The social situation in the European Union 2003
Transcription
The social situation in the European Union 2003
The social situation in the European Union 2003 European Commission Directorate-General for Employment and Social Affairs ACKNOWLEDGEMENTS The Employment and Social Affairs DG and Eurostat would like to thank all those who have contributed to this report, in particular the Health and Consumer Protection DG, the European Foundation for the Improvement of Living and Working Conditions, the Institute for Prospective Technological Studies and the European Centre for the Development of Vocational Training (Cedefop). In addition, the Employment and Social Affairs DG and Eurostat are grateful to the following experts for their valuable contributions to this report: Professor Elias Mossialos of LSE; Professor Géry Coomans of ISMEA; Professor Dr M. Harvey Brenner of the Berlin University of Technology and Johns Hopkins University; Professor Yannis Yfantopoulos of the University of Athens; Professor Christian Haerpfer and Dr Claire Wallace of the Institute for Advanced Studies, Vienna; and Dr Sjoerd Kooiker and Dr Jean Marie Wildeboer Schut of the Social and Cultural Planning Office of the Netherlands. Europe Direct is a service to help you find answers to your questions about the European Union New freephone number: 00 800 6 7 8 9 10 11 A great deal of additional information on the European Union is available on the Internet. It can be accessed through the Europa server (http://europa.eu.int). Cataloguing data can be found at the end of this publication. Luxembourg: Office for Official Publications of the European Communities, 2003 ISBN 92-894-5263-3 ISSN 1681-1658 © European Communities, 2003 Reproduction is authorised provided the source is acknowledged. Printed in Belgium PRINTED ON WHITE CHLORINE-FREE PAPER Table of contents Foreword 5 Section 1 The social situation in brief Introduction 9 1.1. Key social developments 11 1.2. Health and health care in the European Union 16 1.3. The resilience of the European Social Model 26 Section 2 The social dimension of health 2.1. Health trends of the European population 29 2.2. Socio-economic determinants of health 51 2.3. Healthcare systems in Europe 69 2.4. Society and health 89 Section 3 Areas of social policy concern – statistical portraits 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. Annexes Annex I Annex II Annex III Annex IV Annex V Annex VI Economic situation Demography, household and families Ageing of the population Migration and asylum Education and its outcomes Lifelong learning Employment Employment of older workers Unemployment Youth unemployment Long-term unemployment Social protection expenditure and receipts Social benefits Labour market policy expenditure Income distribution Low-income households Jobless households and low wages Women and men in decision making Employment of women and men Earnings of women and men Life and health expectancies Accidents and work-related health problems Key social indicators per Member State Statistical data – European Union Member States Key social indicators per acceding State and candidate country Statistical data – European Union acceding States and candidate countries Symbols, countries and country groupings, other abbreviations and acronyms Eurostat Data Shops 3 107 110 114 117 120 122 125 128 131 134 136 138 140 143 146 148 151 154 156 159 162 165 168 173 175 177 195 197 207 209 Foreword The Social Situation Report – published annually since 2000 – provides the most comprehensive overview of the social dimension in the European Union. It provides a holistic view of the population and its social conditions as a background to social policy development and contributes to the monitoring of developments in the social field across Member States. Furthermore, it establishes links to other Commission publications such as Employment in Europe, Industrial Relations in Europe and the Gender Equality Report. One special characteristic of this report is that it combines harmonised quantitative information with survey data on public opinion. In this way it acts as a reference document, with the perceptions and attitudes of people living in Europe added to the overall portrait of the social situation. This year the report focuses on analysis and research on the health of people living in the European Union. In addition, the report contains extensive statistical information at EU level, which provides a powerful tool for monitoring social developments over time. Anna Diamantopoulou Member of the Commission Employment and Social Affairs Pedro Solbes Mira Member of the Commission Economic and Financial Affairs, Eurostat 5 The social situation in brief Section 1 Section I The social situation in brief 7 The social situation in brief Section 1 Introduction The fourth annual report on the social situation in the European Union contains three sections. Section One presents an executive summary of the key social and economic developments in Europe, with facts and figures at European level. It also gives a synthesis of this year's special theme, which relates to the questions of how and why the health of European citizens has improved, along with some potential future challenges. Section One then concludes with a brief consideration of the European Social Model. Section Two provides a more detailed examination of developments in social trends related to health. Analysis and research, both quantitative and qualitative, are presented under four headings: health trends of the European population; socio-economic determinants of health; healthcare systems in Europe; and society and health. As in previous years, Section Three presents a set of harmonised social indicators for each Member State, which provide an initial overview of the social situation. In addition, they provide a powerful tool for monitoring social developments over time. 9 The social situation in brief Section 1 1.1 Key social developments 1.1.1. The social situation: opportunities and challenges advantage of the opportunities created for continuing on a path of sustainable growth and steady improvements in the social situation1. The social situation is largely formed in the cross-field between longer-term developments in population structures and short to medium term changes in the economy. 1.1.2. Developments in the demography of Europe will impact significantly on the social situation and present major challenges for the European economy. After five years of strong economic growth, which created 12 million jobs and raised the employment rate by four percentage points to 64.0% of the working age population, the outlook has now become less optimistic. In 2001 the rate of economic growth dropped to 1.5%, or less than half the level it achieved in 2000 and in 2002 recovery has been rather slow. Yet employment continued to grow, albeit slowly. The EU population is ageing…. The EU population is ageing and old age dependency rates will increase. Although fertility increased slightly from 1.45 children per woman in 1999 to 1.47 in 2001, it is still well below the replacement level of 2.1. Life expectancy is growing and mortality is increasingly concentrated in old age. As the baby-boomers reach retirement age there will be growing numbers of people in the elderly age groups. Today, people aged 65 and over represent 16% of the total population while those below 15 represent 17%. By 2010 these ratios will become 18% and 16%. The most dramatic increase will occur in the number of 'very old' people (aged over 80), which will rise by almost 50% over the next 15 years. Meanwhile, the medium term economic and social challenges to society from the ongoing ageing of the European population are becoming clearer. Soon the century long growth in the size of Europe's working age population will come to a halt. And in less than a decade the impact of the retirement of the baby boomers will begin to be fully felt. The structural improvements achieved since 1996 and the successful launch of the single currency have resulted in a better economic performance in monetary and financial terms and increased flexibility in the labour market. Beyond the obvious contributions to improvements in living conditions, policy opportunities were enhanced in a number of areas. New possibilities emerged for tackling structural problems in employment, such as youth unemployment and the low activity rates of women and older workers. Higher employment has also eased the pressure on social protection systems and created increased scope for manoeuvre in pension reform. Inequality did not rise during prosperity and rising employment rates and economic growth have produced new possibilities for addressing persistent problems of poverty and social exclusion. …and despite the younger age structure of acceding States, enlargement will not change this trend. As a consequence of high fertility levels in the 1970s and 1980s the acceding States presently have a younger age structure than EU-15 (population aged 65+ amounts to 13% while children below 15 years constitute 19%). Consequently enlargement will have a rejuvenating effect. However, this effect will be both small and temporary. In the medium to long-term acceding States will tend to reinforce the population decline of the EU. Given the onset and persistence of extremely low fertility levels the proportion of children in the population is rapidly declining and by 2020 the share of older people will approach EU-15 levels. The same period has witnessed significant improvements in the ability of Member States to draw support for their policy efforts from the EU. Collaboration on combating social exclusion and modernising social protection have been added to the processes of macro-economic coordination and employment, creating the potential for a virtuous triangle of mutually reinforcing economic, employment and social policies. At the same time families are becoming less stable and households smaller… The rising old age dependency rates will impact on our ability to cope with caring needs, which may also be exacerbated by developments in family and household structures. There are fewer and later marriages, and also more marital breakdowns. In 2001, there were only 5 marriages per 1,000 inhabitants in EU-15 compared with almost 8 in Major challenges persist and with enlargement new ones are emerging. Decisive action is required to maintain the achievements of the last five to seven years and to take 1 Population dynamics A full assessment of the overall situation of the European Union in early 2003 is given in "Choosing to grow: Knowledge, innovation and jobs in a cohesive society" Report to the Spring European Council, 21 March 2003 on the Lisbon strategy of economic, social and environmental renewal, COM(2003) 5 final . 11 Section 1 The social situation in brief Graph 1 14 Years gained 14 Men Women 12 10 8 8 6 6 4 4 2 2 0 …and they are taking steps to address these at the national as well as at EU level. 12 10 The general assessment of present policy efforts is that most Member States – and acceding States – plan to take advantage of the window of opportunity before the large cohorts of baby-boomers reach pension age. They intend to enable their pensions2, health and long term care3 systems to continue to perform their social objectives and retain their financial sustainability when the pressures from ageing rise. Several major reforms have already been carried out and many are under preparation. 0 P Source: their national policies accordingly. Acceding States are shadowing these new collaborations on ageing issues in many areas. Increase in life expectancy between 1960 and 2000 E I F L A EU-15 FIN D EL B IRL S UK NL DK Eurostat. 2000 data: estimated value for EU-15. 1999 data for DE and GR. 1960 data for DE excluding ex-GDR 1.1.3. 1970. Furthermore, the estimated divorce rate for marriages entered into in 1960 was 15%, whereas for marriages entered into in 1980 the figure almost doubled to 28%. The trend towards smaller households, with more people living alone at all ages, is continuing. Also there is a striking rise in the number of children living with one adult, and a fall in the number of couples with children. In 2000, 10% of children aged 0-14 years were living with just one adult compared with 6% in 1990. The overwhelming majority of these single parents are women. With the exception of Poland and Cyprus families have also become substantially less stable in the acceding States. In 2002 unemployment increased slightly for the first time since 1996. Yet, despite the economic downturn labour markets showed remarkable resilience. More jobs were created than lost and the net result was a gain in employment. This suggests that the development and application of the European Employment Strategy and the new emphasis on promoting social inclusion has helped the Union to move to a path of sustainable and higher employment growth amounting to 1.3% per year since 19964. The employment rate increased to 64.0% in 2001 and is likely to reach to 64.5% in 2002; the unemployment rate declined to 7.4%, the lowest rate for a decade, and although it increased in 2002, the rise to 7.6% was very slight5. …while migration flows play an increasingly important role in population change. For more than a decade net immigration has been the main factor in population growth in the Union. Today, all Member States receive significant migratory inflows and in 2001 the annual net migration rate was 3.1 per 1,000 population, representing around 74% of total population growth. In some acceding States emigration has had a noticeable impact on the demographic situation. In particular, the Baltic States have experienced a decrease in population due to emigration. The employment rate average for all countries in the enlarged Union is somewhat lower than the average for the fifteen current EU Member States. However, certain structural weaknesses exist which, although their scale may differ, are largely common to both existing and future Member States. The outstanding challenges that the future Member States face are to increase labour force participation and employment, to facilitate labour flows from agriculture and industry to services without increasing regional disparities in the mediumterm and to upgrade and update skills to the needs of modern knowledge based market economies. Policy makers are becoming much more aware of the consequences of ageing… Awareness of population ageing and its likely impact on employment and social policy has grown significantly in the last couple of years. Member States have committed themselves to work on ageing issues in the context of sound public finances, employment and social protection (i.e. pensions, health and long-term care) and reviewing 2 3 4 5 Recent employment trends Further progress in meeting the Lisbon agenda including full employment calls for decisive action to raise participation and employment, foster quality and productivity at work and to promote cohesion. Proposal by the Commission for a Joint Commission-Council report on adequate and sustainable pensions, COM(2002) 737 final. Proposal for a joint Commission-Council report on: Health care and care for the elderly: Supporting national strategies for ensuring a high level of social protection, COM(2002) 774 final For a fuller assessment of employment developments in this period see "Taking stock of five years of the European employment strategy", COM (2002) 416 final. A proposal for a future employment strategy in view of present uncertainties is given in The future of the European Employment Strategy (EES)"A strategy for full employment and better jobs for all" COM(2003) 6 final. 12 The social situation in brief Section 1 Maintaining labour supply will increasingly depend on raising the activity and employment rates of women… ductivity gains will come to play a key part in economic growth. Immigration will also be an important factor in that respect, particularly when present labour reserves among the existing working age population are fully engaged. Obviously the positive economic and social effects of immigration hinge on the ability of Member States to secure the full integration of newcomers and their dependants into employment and the wider social fabric of European societies. Successful integration of immigrants can assist the maintenance of economic growth and reinforce social cohesion. Between 1996 and 2001, the EU employment rate for men and women increased by almost three and five percentage points respectively, thus narrowing the gap between the sexes to 18 percentage points. As for unemployment the gender gap also declined but remained significant at 2.3 percentage points in 2001. These recent reductions in gender gaps are an encouraging sign that the gap in unemployment rates could be closed in the near future. Growth in employment also entailed the creation of more quality jobs There is also a gender gap in the acceding States, however, the proportion of women in the workforce is higher than in EU Member States (46% compared to 42%). The proportion of women employed in managerial occupations is also higher: 38% of managers in acceding States are women, compared to 34% in the EU. Furthermore, in the acceding States, part-time work is less frequent and more equally divided between the sexes: 6% of men (7% in the EU) and 9% of women (32% in the EU) work part-time. More than two-thirds of the new jobs created between 1996 and 2001 were high skilled as the knowledge economy became everyday reality. Over 50% of all jobs now require the use of a computer. Indeed, recent Commission work has shown that EU economies with higher shares of jobs of higher quality also perform better in terms of employment and productivity. There are also a considerable number of jobs of lower quality. While for the young and the high skilled such jobs often function as a stepping stone into more stable employment, this is not so for older and unskilled workers. When these groups hold temporary contracts, work involuntarily part-time or in jobs that do not offer training, they remain in cycles of unemployment, inactivity and low skilled employment. Hence effort to promote upward mobility into higher skilled and quality jobs is an important element in promoting higher and more sustainable employment levels. ...and older workers… Overall, 38.5% of the EU population aged between 55 and 64 were in employment in 2001. This is well below the Stockholm target of 50% by 2010. The average age at which people leave the labour market was 59.9 years in 2001. It will be a challenge to increase this by about five years by 2010 as the Barcelona European Council has requested. Recent improvements in the employment of older people in some Member States demonstrate that the trend to declining employment participation can be reversed if efforts are intensified. In the acceding States the employment rates for workers aged 55-64 are even lower, but in the last couple of years they have stabilised and begun to improve. 1.1.4. Measured by developments in income and consumption, living conditions continue to improve. The average annual increases in income per capita have oscillated around 1.5% during the last decade with the median net annual income in EU-15 at about 11,700 PPS6 in 1998. Obviously this median covers considerable disparities among Member States and considerable inequalities within the Member States. The northern half of the Union reported higher income levels, and tended to have smaller income inequalities than the southern Member States. Likewise mean consumption has increased markedly in recent years. In Germany, for example, which is fairly typical among Member States in this respect, it grew by about 2.6% per year at household level. From a different perspective - i.e. given current and future population dynamics leading to a shrinking population of working age - it is of great importance that most Member States have considerable labour reserves among women and older workers. If existing barriers to participation are removed, these labour reserves could be used to counteract the impact of ageing on the size of the workforce. ...as well as on the size and shape of immigration and the integration of immigrants. Living conditions are reflected in citizens' perceptions of their quality of life. Demographic scenarios - based on the hypothesis of stable immigration inflows and assuming that the Lisbon employment targets are met - tend to show that, beyond 2010, the overall volume of employment in EU-15 would be reduced as a result of a shrinking working-age population. More so than previously, pro6 Living conditions In 2002 Europeans were very or quite happy with their lives in general (78% against 77% two years earlier) and of these some 20% (against 17% in 2000) were very satis- Measured in Purchasing Power Standards to correct for purchasing power disparities between the countries considered. 13 Section 1 The social situation in brief fied. The most satisfied people live in Sweden (95%) and Denmark (94%) whereas the level of satisfaction is least pronounced in Portugal (50%) and Greece (49%). As in previous years men appear to be happier with their lives than women, and young people more satisfied than the elderly. Of the variations in perceived quality of life across the EU-15, a large amount can be explained by differences in perceived health status. necessary. This subjective poverty measure varies widely across Member States - between 9% in Denmark and 66% in Portugal. The survey also shows that, at the individual level, the duration of poverty tends to be longer in southern countries (fourteen or fifteen years) compared to northern countries (two to three years). The Eurobarometer furthermore documents that poverty is closely related to social isolation and that it is strongly affected by poor quality of employment, in particular poor task quality, job precariousness and insufficient training. People with a higher education and those with higher income score higher in terms of perceived health and life quality, reflecting inequalities due to socio-economic status. Additionally, perceived health is generally lower amongst the elderly. Social inclusion is closely linked with employment and/or income. It is noteworthy that in the knowledge society new technologies represent both an opportunity for and a threat to the inclusion of disadvantaged people. Work done by ESDIS (High Level Group on the Economic and Social Dimension of Information Society) has highlighted this and it has been given political prominence with Council Resolutions on e-Inclusion in October 2001 and eAccessibility for people with disabilities in 2002. Most respondents to the Eurobarometer 2002 give a higher priority to public spending on health care than other areas such as education or social assistance and consider that the quality of the health care system is one of the three most important issues facing society today. 1.1.5. Trends in income distribution …and differ markedly across the Union… Income is one of the main factors in determining the standard of living. The distribution of income is also important in relation to relative poverty and risks of social exclusion. The Welfare State plays an important role in the redistribution of primary income, thereby reducing inequality and poverty. A recent report7 reveals that large changes in income inequality occurred within many countries between 1980 and 1997 - in most cases income inequality increased. During the economic growth in the second half of the 1990s it is remarkable that inequality on average tended to decrease. Poverty rates of households differ considerably between Member States (based on 60% of national median equivalised income as the poverty threshold). In 1998 the difference between the Member States with the highest and the lowest poverty rate amounted to 14 percentage points. Between 1995 and 1998, six out of twelve Member States that have data for both years lowered their poverty rates. Nevertheless, the overall EU-15 poverty rate in 1998 was the same as in 1995. In general, the southern Member States have the lowest mean equivalised net income in PPS but also the highest level of income inequality according to the 1998 wave of the European Community Household Panel (ECHP). The Scandinavian Member States show the lowest inequality while the highest mean equivalised net income is found in Luxembourg, Belgium and the Netherlands. Obviously this may reflect that recent economic growth to a large extent has been employment driven. Employed people are the least likely - and unemployed the most likely (five times more likely) - to be living at risk of poverty8. In 1998 retired and self-employed people were twice as likely to be living at risk of poverty than the employed, children three times more likely and the other groups of economically inactive people four times as likely. …but in EU15 they would be much higher without the redistributive impact of social benefits. Risks of poverty and social exclusion persist… The redistributive effect9 of social protection benefits substantially exceeds the redistributive effect of taxes. Social benefits reduce income inequality, measured by the Gini-coefficient10, by about 30% to 40%. The regressivity of the benefits is relatively large in Germany, the Netherlands, Belgium and the United Kingdom: households with low incomes in these countries receive a relatively higher proportion of social benefits than in Finland, Denmark and Sweden. However, in the case of Germany Despite the important redistributive effects of social protection, combating poverty and promoting social inclusion remain among the key challenges facing the Union. Recent findings from the 2001 Eurobarometer survey reveal that a high proportion of people still consider themselves poor, in the sense that their net income is lower than the amount they judge absolutely 7 See "Income on the Move", report on income distribution, poverty and redistribution, Social and Cultural Planning Office of the Netherlands, funded by the European Commission, DG Employment and Social Affairs (E1 Study Series 2002), http://www.europa.eu.int/comm/employment_social/news/2002/dec/income_on_move_en.html 8 With risk of poverty defined as having less than 60 % of the median equivalised income. 9 The results are taken from "Income on the Move" and refer mainly to the 1997 wave of ECHP. 10 The Gini-coefficient is an index comparing the actual income distribution all across the entire income range with a kind of theoretically ideal distribution where everybody has the same income (gini = 0 %). A 100 % Gini would mean that only one person has all income. 14 The social situation in brief Section 1 and the United Kingdom the inequality reduction between the distributions of market and gross income is rather moderate. This is because the share of social security in national income in these countries is relatively low. ...as have the possibilities for drawing support from EU collaboration have grown substantially. The importance of addressing these problems was recently underlined by the adoption of revised appropriate EU objectives for the fight against poverty and social exclusion by the Council in December 2002. The revisions reinforce the objectives first adopted at the Nice European Council in 2000 and also gave increased emphasis to the gender dimension, the difficulties facing immigrants and the importance of reducing the number of people at risk of poverty and social exclusion. These objectives will underpin the preparation of a second generation of twoyear National Action Plans against poverty and social exclusion, which should be drawn up by all Member States by July 2003. The intention is to build on and consolidate the progress made by the Open Method of Coordination on poverty and social exclusion which was launched by the Lisbon European Council in 2000. Benefits exist in many categories and differ in the number of recipients and in the mean amounts. The poverty reduction of all benefits together, measured simply by comparing ‘before’ and ‘after benefit’ income, is 25 percentage points11. The main part of poverty reduction is claimed by old age and survivors' benefits (15 points). Unemployment, family related and sickness / invalidity benefits each resulting in equal effects of about three points reduction of poverty. 1.1.6. Trends in the acceding States Although most of the acceding States have made gains in closing the income gap in relation to the European Union Member States during the second half of the 1990s, differences are still considerable. In 2000, in eight acceding States the GDP per capita was below half of the EU average, measured in purchasing power standards. Enlargement from EU-15 to EU-25 is now on the immediate horizon. With it we can expect to see significant changes in the overall social situation of the Union. Policy challenges in combating social exclusion, poverty and different forms of inequality, including inequalities in health status are set to increase. Regional inequalities and problems with social cohesion will be more important. Thus, as disparities between Member States will increase considerably there will be a great need for instruments of collaboration to bridge such differences in a constructive way. Moreover, the income distribution in the acceding States has tended to become more unequal. This is particularly true for the eight central and eastern European acceding States12. Over the last decade Eastern Europe has experienced significant increases in both poverty and inequality. Lately the situation has stabilised. Inequality and poverty are no longer increasing, but the social consequences of the rapid growth in inequality in the early transition period need further attention. Awareness of these problems has been growing… Poverty is on the policy agenda in all acceding States, but the wider concept of social exclusion alluding to multideprivation less so. Social exclusion has, however, risen in policy prominence in recent years, often as a reflection of EU policy making. The major factors leading to social exclusion are unemployment and family breakdown, and the limited ability of social protection and employment to ensure adequate income and resources in many of the acceding States. In addition inadequate coverage and performance of social assistance schemes often make it very difficult to tackle problems of social exclusion. 11 This figure is illustrative of the magnitude, yet since there are other variables which influence the two situations, one cannot attribute the difference between the two Gini coefficients solely to the effect of social benefits. 12 European Commission, "Making a success of enlargement", Strategy Paper and Report of the European Commission on the progress towards accession by each of the acceding States, p. 13. 15 Section 1 The social situation in brief 1.2 Health and healthcare in the European Union 1.2.1 The Health of Europeans and the Current European Agenda Obviously, the effect of investments in health depends not just on how much is spent, but on where, when and how resources are committed. The return on investments in better health can – inter alia – be particularly large if efforts are directed at social groups or regions where the average health status is poor or particularly threatened. Inequality in health status is linked to wider inequalities in society. Poor and excluded people are particularly affected by poor health. Member State policies aimed at combating poverty, reducing inequalities and promoting social inclusion and the new European collaboration on these issues impact positively on the health status of poor people and improve the level of social cohesion in society. Health is the special theme of this year's report. Health and the quality of health care are very high priority concerns for Europeans (Eurobarometer 2002). This report portrays the health status of Europeans and identifies the main determinants of their health. While the health sector is key in the treatment of poor health, and also plays a role in the maintenance of good health, the overall health status of citizens is significantly shaped by socio-economic, lifestyle and environmental conditions. The organisation of health and long term care varies greatly across the Union. Amid these differences there are also substantial similarities and - as the report demonstrates - Member States are faced with largely the same current and future challenges in health policy. Among these, two stand out as particularly pertinent. On the one hand there is a continuous need to optimise the cost-effectiveness of health care systems in the face of strong drivers of structural change such as ageing and new health technologies. On the other there is great scope for developing better synergies between health policies and other policies that influence the environmental and socio-economic determinants of health. In these ways health and health care are located at the intersection between the European Employment Strategy and the Union's efforts to modernise and improve social protection. Conditions for acquiring good health status and for receiving appropriate and effective treatment for illnesses have improved substantially in the European Union over recent decades. This is due to public and private efforts through direct investments in better health care. However, while health care systems play a crucial role in the combat and prevention of ill health, other policies, which affect the environmental and socio-economic determinants of good health, like employment and working conditions, also impact significantly on the present and future health status of citizens. Health is wealth The health status of citizens is an important factor in the productive capacity of society and health improvements can improve the potential for growth.13 This is because better health holds the potential for higher productivity, longer working lives and lower cost (less absence due to illness, less need for treatment, less disability, etc.)14. Health care is part of the social protection systems in Member States. As such it is a topic in the new collaboration15 on the modernisation and improvement of social protection, which form part of the wider Lisbon strategy. Accessibility, quality and sustainability have been pinpointed as the common goals that Member States are striving for in their health care policies. The income maintenance effect of social protection systems clearly also help sustain the health status of citizens. Pension systems, for example, contribute greatly to the maintenance of the health of older citizens by facilitating a sufficiently sound standard of living after retirement. 13 An assessment of this relation pertaining to the world is given in the Report of the Commission on macroeconomics and health - chaired by Jeffrey D. Sachs (2001): Macroeconomics and health: investing in health for economic development. WHO, Geneva. 14 An American review of the scientific literature of the last decade leads to the conclusion that in the US workers with good health earn 15% to 30% more than workers in poor health: Jack Hadley (2002): Sicker and Poorer: the consequences of being uninsured. A review of the research on the relationship between health insurance, health, work, income and education. The Kaiser Commission on Medicaid and the Uninsured. 15 Proposal by the Commission for a Joint Commission-Council report on adequate and sustainable pensions, COM(2002) 737 final. Also, proposal for a joint Commission-Council report on health care and care for the elderly: Supporting national strategies for ensuring a high level of social protection, COM(2002) 774 final. 16 The social situation in brief Section 1 The European policy agenda on Health does not prevent basic freedoms - such as freedom of provision of services, circulation of medical products, or of movement of workers - or other Community policies, from applying to this area. Policy developments during the previous decade brought health issues to the fore of the European agenda. In the Maastricht Treaty (1993) public health was given a legal base for the first time (Article 129), encouraging cooperation among Member States, prevention of diseases and incentive measures. No harmonisation of laws and regulations was included. Responding to these new obligations the Commission presented its "Communication on the Framework for Action in the Field of Public Health16" based upon the establishment of eight Public Health Programmes. The EU-level added value through support for efforts pursued in Member States and dissemination of "best practice information", with a view to continuously underpin health protection provisions across the Community. Moreover, health is a crosscutting issue in the European Social Agenda and an important item in the EU strategy for sustainable development, both of which constitute important elements in the Lisbon strategy. In addition healthcare has become an issue in cross border mobility and in the effort for improving public finances. The quality and sustainability of healthcare has been acknowledged as one of the key issues for closer co-operation among the Member States. At the Gothenburg European Council (June 2001) the Social Protection Committee and the Economic Policy Committee were asked to consider the challenges of an ageing society and to prepare an initial report for the Spring 200220 European Council on orientations in the field of healthcare and care for the elderly. The report concluded that the underlying demographic, technological and financial factors present health care and long-term care systems in the European Union with challenges that focus upon: access for all regardless of income or wealth; a high level of quality of care; and financial sustainability of care systems. At the end of the 1990s the general framework of health policy changed. The Treaty of Amsterdam expanded the powers of the Community in the public health field. Article 129 was revised through the addition of several new provisions and renamed as Article 152. According to Article 152 actions in the public health area should: contribute towards ensuring the attainment of a high level of health protection; improve health; prevent human illness and disease; prevent sources of danger to health and ensure that all EC policies protect health. These three broad goals were endorsed by the Council in an initial orientation report on healthcare and care for the elderly to the Barcelona European Council which also stressed that all health systems in the EU are based on the principles of solidarity, equity and universality. The Barcelona European Council asked the Commission and the Council to examine more thoroughly the questions of access, quality and financial sustainability. Based upon a questionnaire submitted to the Member States the Commission proposed a joint report on national strategies to ensure a high level of social protection.21 Since healthcare accounts for a large proportion of public spending, the financial sustainability of care systems and their reforms in this regard are important. In this overall context, in May 2000 the Commission proposed a new health strategy17, which promotes an integrated approach to health related-work at Community level. A key element of this was a proposal for a new programme of Community Action in the field of public health18. The programme will be focused on three main strands of action: – – – Improving health information and knowledge for the development of public health. Strengthening the capability for coordinated, rapid response to major health threats. Targeting actions to promote health and prevent disease. Health and Safety at work is one of the most important dimensions in European social policy. Health at work is not only the absence of accidents or occupational illnesses, but involves physical, moral and social wellbeing, which are important for the quality of work and for the productivity of the workforce. A new Community strategy on health and safety at work for the period 20022006 has been developed, taking into account changes in society and the world of work22. The strategy adopts a global approach to wellbeing at work, based on preventative measures and building partnerships between all players in the areas of employment, health and safety. In addition, the Commission has created an EU Health Forum that brings together relevant European organisations. Furthermore, the sixth Framework Programme for Research provides for policy-orientated research which is relevant to the area of social policy, relating in particular to the implementation of the European Social Agenda19. The responsibility for health care provision and funding lies with Member States. However, this responsibility 16 17 18 19 November 1993. COM (2000) 285 final of 16.5.2000 OJ L 271/1 of 9.10.2002, Decision 1786/EC. See the specific programme for research, technological development and demonstration: Integrating and Strengthening the European Research Area (2002-2006). 20 Based upon COM(2001) 723 final: The future of health care and care for the elderly: guaranteeing accessibility, quality and financial viability. 21 COM(2002) 774 final. 22 COM(2002) 118 final: Adapting to change in work and society: a new Community strategy on health and safety at work 2002-2006. 17 Section 1 The social situation in brief 1.2.2. Population and health cies are beginning to converge. This has already been observed at EU-15 level (where life expectancy at birth increased 2.5 years for men between 1990 and 2000, compared with 2 years for women) and in all Member States except Greece, Spain, Luxembourg and Portugal. The health status of citizens has improved in all EU Member States over the last decades... The average health status of EU citizens is improving. In 2000 the average life expectancy at birth for the EU-15 was 78 (75 for men and 81 for women). This is higher than in the USA (74 for men, 80 years for women) but lower than in Japan (78 years for men, 84 for women). As a result of increasing life expectancy combined with changes in fertility, the EU population is increasingly older. This demographic ageing means that the number of older people is growing while the share of those in working-age (15 to 64) will decrease. These demographic trends will have economic and social consequences in a number of areas, including health and care systems. Life expectancy at birth is not only a social indicator. It is also an important economic indicator. Analysis on macroeconomics and health shows that health status explains an important part of the difference in economic growth rates.23 Graph 2 For the provision of healthcare, one of the most important demographic trend is the increasing size of the very old age group (over 80 years old). It will increase by eight million between 2010 and 2030, an increase of 44%, i.e. a growth even larger than that experienced by the older population in general. Presently the majority of these very old people are in need of assistance and care, which is either provided formally or informally - the latter of these includes care from family members, which is particularly evident in southern Member States. In the future, households will reduce in size and families may be less able to shoulder the increasing care tasks, making the role of both formal and other informal carers of greater importance. The ageing process has a strong gender dimension: the vast majority of these very old people will be women. As the population ages women's health problems will weigh substantially heavier in the pattern of illnesses to be treated and tackled. Life expectancy, men and women. EU-15, 1960-2000 90 90 85 85 Women 80 80 75 75 70 70 Men 65 65 60 60 55 55 50 50 1960 1965 1970 1975 1980 1985 1990 1995 2000 Source : Eurostat. ...leading to new patterns of mortality and morbidity trends. The figure on life expectancy has increased during the 20th century: an increase of 25 years was achieved in the first 60 years of the century, while in the last four decades eight more years were gained24. Male life expectancy increased from 68 years in 1970 to 75 years in 200025. During the same period female life expectancy increased by 6 years, from 75 years in 1970, to 81 in 2000. As people are living longer, mortality and morbidity are shifting towards increasingly older ages. The main causes of death are diseases of the circulatory system (around 40% of all deaths), cancer (a quarter of all deaths), diseases of the respiratory system, digestive diseases and external causes of injury and poisoning, which includes (car) accidents26. One out of every five deaths is caused by a preventable disease. However, this general pattern varies by sex and, especially, by age. Mortality during the first year of life has decreased in recent decades in all Member States, where present levels are among the lowest in the world. However, given the persistence of differences in these existing infant mortality levels among social groups or territories, further improvements can still be achieved. Lower life expectancy for men is caused by male overmortality at all ages, which is a well-known phenomenon in all Member States and also in the majority of other world nations. These inequalities by sex, although conditioned by biological factors, are mainly attributable to social causes and to certain lifestyle patterns. Now that the behaviour of men and women in the EU is becoming more similar, male and female life expectan- 23 Report of the Commission on macroeconomics and health - chaired by Jeffrey D. Sachs (2001): Macroeconomics and health: investing in health for economic development. WHO, Geneva (p 24) : " In particular, each 10 % improvement in life expectancy at birth is associated with a rise in economic growth of at least 0.3 to 0.4 percentage points per year, holding other growth factors constant". 24 The nature of the indicator partly explains this slow-down. For a given year, life expectancy is the average age that a new-born baby may expect to live to if the mortality rates of this given year were maintained. As the total number of years of life lost by a person who dies in the first year of life is much higher than the years lost by a person who dies, for instance, at 65 years old, life expectancy is more sensitive to the reduction of infant mortality than to increasing longevity at older ages. 25 However, the increase in life expectancy stopped during the second half of the 1980s and early 90s for men in some southern Member States as a consequence of the increase of mortality caused by AIDS and traffic accidents, which affect young men in particular. 26 Source: Eurostat. Also see the DG Health and Consumer Protection report "The health status of the European Population" EC 2001. 18 The social situation in brief Section 1 Graph 3 1990-2000 2000-2010 2010-2030 30 30 25,1 25 25 20 20 13,7 (millions) 15 15 7,9 10 4,4 5 6,1 8,1 8,2 8,3 4,8 0,0 -10 10 5 1,5 0 -5 in the existing EU Member States. There are large differences among the acceding States and candidate countries, with Malta and Cyprus in the best position (comparable to, or even better than some existing Member States), followed by Slovenia, whereas the Baltic States, Romania, Bulgaria and Turkey have a poorer health situation. This is reflected in higher infant mortality rates and lower life expectancy, as well as higher incidence of non-infectious diseases (especially heart disease, diseases of the circulatory system and cancer), infectious diseases (including in some countries sexually transmitted diseases and tuberculosis) and violent deaths. Population change (in millions) by age group. EU-15 0 -5 -3,0 -3,5 -4,9 -5,4 -6,9 -10 -10,6 -15 -15 -20 -20 -18,3 -25 Future disability trends will relate more to oldage risks. -25 0-14 15-29 30-49 50-64 65+ 80+ Note: B:1995, DK: 1996, EL: 1997, E, F, IRL, I, S,UK, EU: 1998 Source: Eurostat Graph 4 It is a feature of human life that the number of functional disabilities of all kinds tends to increase with age. Sickness, risky lifestyles, accidents and socio-economic factors all combine to create a 'disabling' process, which accumulates over time. It is not surprising, therefore, that young people make up 5% of the people with disabilities, while people of working age constitute 46% and the remaining 49% of the people declaring disability are over 60 years of age (ECHP Data). With increasing life expectancy, prevalence of visual and hearing impairments also increase, as well as neurological disorders such as Alzheimer's disease and dementia. However, future trends in age-specific risks of becoming hampered will be a key factor in the number of elderly people that will be in need of assistance and care. Population change (in %) by age group. EU-15 1990-2000 2000-2010 2010-2030 60% 60% 44% 36% 40% 20% 14% 7% 12% 8% 16% 14% 35% 40% 20% 12% 0% 0% 0% -5% -20% -5% -8% -7% -10% -13% -20% -16% -40% 1.2.3. -40% 0-14 15-29 30-49 50-64 65+ The determinants of population health 80+ Source: Eurostat Health developments are to a large extent determined by environmental conditions... However, as infant mortality is currently very low, further increases in life expectancy are now dependent on reducing morbidity and mortality at older ages. People in Europe are facing health risks from their physical environment, which to a very large extent are due to prevailing patterns of life and inherent use of resources. Human health depends on the availability of quality food, water, air and shelter. It is also affected by noise, traffic congestion and accidents and insufficient sewage systems. Rapid urbanisation has created particular problems in many cities, resulting in air pollution and unacceptable housing conditions. Other health problems relate to water and food contamination, causing communicable diseases. However these adverse effects are being continuously addressed through urban renewal, improved infrastructure, monitoring of pollutants and reinforced food safety measures which have reduced their prevalence. The major causes of morbidity are neuro-degenerative diseases (such as Alzheimer's and dementia), injuries, cardiovascular diseases, musculoskeletal diseases and cancer27. As most of these diseases are positively agerelated, population ageing will impact on the morbidity pattern and needs for healthcare. Mental health problems are also increasingly significant. In the EU, about a quarter of new disability benefits are attributed to mental ill-health. The health situation is also changing in the acceding States and candidate countries. During the last decade, air pollution in central and eastern European urban areas decreased due to the adoption of several technical measures and of economic Health status is also improving in the acceding States, but, in most cases, they are generally lower than those 27 Source: Eurostat. Also see the DG Health and Consumer Protection report "The health status of the European Population" EC 2001. 19 Section 1 The social situation in brief Graph 5 Employment overall has a positive impact on longevity and health, provided that jobs are of high quality. Low quality of work is shown to create specific occupational health problems (accidents, injuries and occupational diseases). The main work-related health problems are musculoskeletal, followed by stress, then pulmonary and cardiovascular disorders. The type of industry and occupation, the type of work contract (temporary) or work time (shift work), age and gender influence the prevalence and incidence of disease. Although women represent 46% of the workforce, the female share in occupational diseases is 18% on average, although this also reflects differences in working hours. Main determinants of health28 Age, sex, hereditary factors Life style Family and community support Living and working conditions Environmental and cultural context The costs of low quality work are considerable. Costs of preventive or curative healthcare should be considered in relation to the number of workdays lost due to work related accidents and bad health and the consequent loss of production and income. In total, accidents and work-related health problems resulted in 500 million lost workdays in the EU in 1998/99. stagnation. However, housing conditions remain below West European standards and traffic problems are becoming very important. In the acceding States a larger proportion of workers consider their health and safety to be at risk because of work: 40% as compared to 27% in the EU30. Work related problems are reported at a higher level in these countries, in particular overall fatigue and musculoskeletal disorders. The health and safety systems in the acceding States will have to adapt to the European legislation. In many of these countries social dialogue is less developed, thus ensuring workers and employers input to improve the system remains a major challenge. ...and socio-economic conditions... Health is clearly related to socio-economic status. This concept is normally defined using a number of interrelated indicators, such as occupational status, gender and levels of education, income and wealth. For the individual the socio-economic status determines the access to social and material resources as well as the exposure to health risks. At the individual level education appears to enhance social capacities, expand individual opportunities, build self-confidence, increase skills and capabilities and promote a healthier lifestyle, by increasing the awareness of risks. According to the Eurobarometer only 50% of people with less than upper secondary education, against almost 75% of people with tertiary education, perceive their health as "good" or "very good". ...and the extent and quality of social networks. Social support is important for health and particularly crucial for good health at both ends of the life cycle. Social networks - consisting of family members, relatives, peers and friends - contribute to protect and enhance the health of individuals. They exert a control on deviant behaviour and on most factors related to lifestyle. They can facilitate access to health and services, provide a large amount of informal care and help attenuate the impact of negative events. Employment and unemployment are both important to health status. High employment rates, or low unemployment, together with high average national wealth, have been shown to reduce mortality rates significantly, within a time lag29. Furthermore, many studies at individual level point to a positive correlation between unemployment and illness or disability, both in physical and mental terms. Unemployed people are far more likely to report bad health and to consult physicians. The mortality risk for people out of employment is higher than that of people in steady employment. There are higher suicide rates among young unemployed people. However, social networks or 'informal jobs' may, to some extent, alleviate the negative impact of job-losses. This 'buffer effect' is stronger in some Member States. The family remains the bedrock of care and support for both children and adults in all Member States and the role of the family in the provision of care is perceived as important and positive. Currently 6% of Europeans spend a large part of their time providing informal long-term care for older people or working-age adults who are sick or disabled. The future ability of families to provide long-term care will be affected by developments in the activity rates of women and increasing instability of family structures. All Member States see a 28 Based on the analysis presented in “Policies and strategies to promote social equity in health” Dahlgren and Whitehead. Institute for Future Studies. Stockholm. 29 Prof. H. Brenner: "Unemployment and public health", European Commission, DG Employment and Social Affairs. 30 Survey on working conditions in the candidate countries, 2001 – European Foundation for the Improvement of Living and Working Conditions. 20 The social situation in brief Section 1 trend towards a reduction in household size and a growth in the number of people living alone. Scenarios for EU-15 show that by 2020 46% of people aged 85 and older will be living alone and 80% of these will be women. As a result, an increasing number of elderly people are likely to be in need of formal care provisions even if disability rates at old age continue to drop. Tobacco smoking is associated with a vast array of, sometimes fatal, diseases that may otherwise have been avoided (cardiovascular diseases, cancers and pulmonary diseases). Overall, one third of the EU-15 population declare to smoke regularly. The smoking prevalence among men is higher than for women in the EU-15 (40% for men and 28% for women) and it is on the increase, for young women particularly. Evidence found for Denmark shows that lung cancer, linked with high female tobacco consumption, is one of the causes of relatively low life expectancy of Danish women33. Strategies aimed at promoting healthy behaviour need the strong involvement of a wide range of stakeholders. To increase public awareness and understanding of risks to health, a balance between government, community and individual action is necessary. The potential for community action by non-governmental organisations, local groups and others should be given due attention. Alcohol and blood pressure account for 9-10% of DALYs34, and cholesterol and body mass for 6-7% of DALYs for both sexes. Inadequate nutrition – i.e. a poor overall dietary pattern – has important consequences in socio-economic terms, contributing to health deficiencies or resulting in economic and social costs. Eurostat data suggests that around 17% of EU adults are overweight and around 6.5% are obese. Being overweight or obese increases the risk of some chronic diseases, such as cardiovascular diseases, certain cancers and diabetes type two. Obesity is on the increase, particularly among children. Recent trends in social exclusion pose new challenges for reducing health inequalities. In poor countries there appears to be a clear association between the level of income and mortality. Higher income is often related to better health. This relationship becomes less obvious in more wealthy countries, where mortality patterns appear to be associated to the degree of income inequality. This is primarily because low income and poverty are associated with poor living and working conditions and poor lifestyle. Poor people are much more likely to describe their health as bad or very bad in most Member States and report a higher level of social isolation, less potential support and lower availability of informal care. ...particularly for the young people... Health improvement for the youth has not followed the same pace as society in general and young people young men in particular - presently face relatively high death rates that are linked with behaviour and lifestyles. Drug abuse, including alcohol, is frequently behind the excessive number of deaths of young people from external causes: mainly car accidents for young men between 15 and 30, but also other types of violent deaths, such as suicides, the second most common cause of death for young men. Furthermore, use of illegal substances is concentrated amongst young adults, especially men in urban settings: the prevalence rate among young adults is roughly twice that of all adults. In addition, sexual behaviour – for example unintended pregnancies and the risk of infection from sexually transmitted infections – is a significant issue in young people's health. Low income and poverty may imply poorer access to preventive (e.g. consultation) and curative (for example medication and hospitalisation) healthcare of sufficient quality – for example treatment, communication and follow-up. Individuals with higher income are more likely to receive specialist services whereas those with lower income tend to use general practitioner care31. Incremental health benefits resulting from reduced income inequality are particularly important when poverty is also present within the society. In policy terms this means that fighting poverty and removing barriers to access to healthcare systems are major health issues. New challenges also relate to the health impact of various lifestyles... …and in the acceding States. Problems with tobacco consumption are significant, with rising numbers of smokers among young people and women. Alcohol consumption is another lifestyle factor that plays a role in many causes of mortality. It is likely that alcohol is a more significant factor in higher rates of sudden cardiac death35 and cirrhosis in central and east European acceding States than in the EU. Life style has an important impact on health status. A number of serious and growing health problems of epidemic proportions relate to poor lifestyles in relation to nutrition, exercise and abuse of alcohol, tobacco and illegal drugs. Tobacco use is the leading risk factor, accounting for about 12% of the total disease and injury burden, according to the latest WHO report32. 31 The issue of access to high quality healthcare also for all vulnerable groups was discussed in the Joint Report on Social Inclusion agreed at Laeken in December 2001. 32 World Health Report – 2002: Reducing risks, promoting healthy life. 33 See the DG Health and Consumer Protection report "The health status of the European Population" EC 2001. 34 The DALY or Disability-Adjusted Life Year is a measure to quantify the burden of disease, which takes into account years of life lost due to premature mortality and years lived with a disability of specified severity and duration. One DALY (lost) is thus one lost year of healthy life. 35 Britton, A. & McKee, M. 2000 'The relationship between alcohol and cardiovascular disease in Eastern Europe' Journal of Epidemiological Community Health 2000, 54: 328-332. 21 Section 1 The social situation in brief Generally speaking, mortality rates from injuries, especially road traffic accidents, drowning and fires, and from homicides and suicides, are also higher in these countries, which may in part be attributed to patterns of alcohol consumption. 1.2.4. Health care systems in Europe rely on a mix of funding sources. Most funding in all Member States is public expenditure (on average 75%) raised through taxation and social health insurance contributions. Private expenditure (from out-of-pocket payments and private health insurance) accounts for less than 30% of total health expenditure, except in Greece, Italy and Portugal. The share of out-of-pocket payments within the overall EU health expenditure increased slightly during the 1990s and in 1998 the EU average was 16%. In Italy and Portugal the share of out-of-pocket payments in total health expenditure is higher than 30%. It seems that, contrary to expectations, cost shifting to private sources of funding has not restrained the growth of overall health expenditure. The importance of healthcare systems Healthcare systems are important for health outcomes and the economy in all Member States... Health care systems are important for combating ill health and contribute significantly to health outcome. Moreover, the weight of the health and long-term care sector in the economy and employment is considerable. On average, employment in the health and social services sector of the fifteen Member States is almost 10% of overall employment. The health sector is also a very dynamic and quickly developing sector of the economy with a substantial potential for contributing further to economic growth and employment opportunities. The health and social work sector contributed to 18% of net employment creation in the EU between 1995-200136. ...and for long term care. It is difficult to establish both costs and national trends for long-term (or tertiary) care because these services are often divided between different public structures and budgets – normally between the health budget and the budget for social services. The best available estimates of public expenditure on long term care point to an EU weighted average of 1.3% of GDP in 2000 and a span from 0.7% in France, Ireland, Austria up to 3% in Denmark and 2.8% in Sweden38. …which despite great differences in the organisation of health care face similar challenges. The organisation of long-term care for the elderly shows considerable variations between Member States. Denmark has a high number of beds devoted to long term nursing care whereas the Mediterranean Member States are considerably below the EU average; this is related to the differing role played by family networks providing informal care. The sector is undergoing rapid changes as services are being reorganised or innovated in northern and central Member States and expanded in the south, partly because of the changes in family patterns. Non-profit organisations play an increasing role in the health and social services sectors. There is a large diversity among Member States in the way health care systems are organised, regulated, financed, delivered and utilised. Nevertheless, there are many similarities in the problems health care systems have to tackle. Population ageing constitutes one particularly important common challenge. Securing access for all to high quality sustainable health and long term care even at the height of population ageing is generally perceived as the common goal that Member States are striving for in their health care policies. Member States spend substantial amounts on health care... Within healthcare services the balance between primary, secondary and tertiary39 care has progressively changed. Secondary (mainly hospital in-patient) care has declined in importance mainly due to progress in therapeutic treatments and improvements in primary care and day care. This raised the need for a greater decentralisation of healthcare provision and for new co-ordination between the stakeholders at national, regional and local levels. The changing relationships between the state, the market and the non-profit sector in health care, with a growing share for the private sector, raises new challenges in terms of regulating and managing health care provision and achieving equity objectives. In 1999 the share of total health expenditures in GDP varied between 10.3% in Germany and 6.1% in Luxembourg, with a weighted average of 8.4%. Total health care expenditure as a proportion of Gross Domestic Product is presently highest in Germany, followed by France and Belgium. In the USA, total expenditure on health reaches 13% of GDP in 2000, with a public share of 44%37. In Canada the figures are more similar to the EU average, with health expenditure 9.1% of GDP, and a public share of 71%. 36 37 38 39 Employment in Europe, 2002. OECD Health Data - 2002. Budgetary Challenges posed by ageing populations - Economic Policy Committee (2001). Secondary care covers the hospital in-patients services; tertiary care covers long term care. 22 The social situation in brief Section 1 vely poor. In theory, entitlements to healthcare benefits have remained universal with comprehensive coverage in most countries. In practice however, services are rationed and informal payments are not uncommon44. There is a certain trend towards the privatisation of health care provision in a number of the acceding States. This is accompanied by more private resources being devoted to health both through out-of-pocket payments and through risk coverage by private health insurance. Most Member States are ensuring universality of access... Universal or near universal rights to health care are found in every Member State. This has been a major achievement within the EU in recent decades. With the introduction of universal coverage in January 2000, France now joins Denmark, Finland, Greece, Ireland, Italy, Luxembourg, Portugal, Sweden and the UK in providing universal statutory health coverage significantly reducing the risk of social exclusion from health services. In comparison, in the USA it is estimated that 40 million Americans or 14% of the population have no health insurance40. 1.2.5 Future challenges to health care systems Health care systems face new challenges to their financial sustainability, quality and accessibility... However, in spite of the universal or near universal character of statutory health insurance coverage, problems of access associated with various gaps in coverage persist across Member States. These problems arise in two ways: as a consequence of the exclusion of particular treatments from statutory health insurance coverage, or as a consequence of increasing reliance on user charges. Demand for health and long-term care have grown over recent decades, mainly as a result of the progress in medical technologies and treatments and the growing expectations of our wealthier societies. Policy makers will also have to address the new structural trend of rising expectations from health care consumers. Changes in lifestyles, patterns of work, incomes, educational levels and family structures are altering people's attitudes towards healthcare. The information society also brings instant access to knowledge about the latest possible treatments to anyone with access to the Internet: health-related web sites are among the most visited on the Internet. Changing attitudes include increased awareness of patients' rights and responsibilities, less tolerance of discrimination and a reduced deference towards health care professionals. There is widespread evidence of a desire for greater choice and more individualised services, along with access to a wider range of medical treatments – including those beyond the traditional boundaries of healthcare systems. As a consequence, it is important to correctly assess and address the underlying health needs of the population, as this can contribute to the elimination of ineffective, or even detrimental, health services from being administered. ...and developing quality standards. Most Member States have made progress in establishing quality standards for healthcare41. However, this has proved to be difficult in some areas, for example with outpatients, and in relation to the introduction of outcome related standards. Pressures to improve the quality of care experienced by patients have continued to grow, as have pressures to contain costs. Increasing awareness that spending on inefficient technologies imposes opportunity costs on other patients has contributed to an increase in the demand for evidence on the budgetary impact and cost-effectiveness of interventions as part of health technology assessment. Quality evaluation of healthcare delivery can be found in one form or another in all EU countries42. The acceding States and candidate countries show different patterns. ...developments in technologies and therapies... Most acceding States and applicant countries spend a lower proportion of Gross Domestic Product on health care than the EU average. It ranges from 2.6% in Romania to more than 8% in Malta. There is a relatively high propensity to hospitalise people in the acceding States mainly due to underdeveloped primary care systems43. However, in many of these countries there are fewer medical staff per inhabitant and the hospital infrastructure and other health care facilities are relati- Progress in medical technologies and treatments have contributed to rising costs over past decades. New technologies can also reduce the costs of treating certain diseases, but they may raise expenditure if they treat conditions for which no treatments or only less effective treatments were previously available, or if they are prescribed for conditions for which cheaper treatment alternatives exist. The impact of new technologies on future healthcare expenditure is difficult to predict, but a more sys- 40 Jack Hadley (2002): Sicker and Poorer: the consequences of being uninsured. A review of the research on the relationship between health insurance, health, work, income and education. The Kaiser Commission on Medicaid and the Uninsured. 41 For a discussion on quality standards please see the European Commission Communication "Health care and care for the elderly: Supporting national strategies for ensuring a high level of social participation" (2003). 42 A detailed discussion on Health Technology Assessment is contained in Section 2.3 of the DG Employment and Social Affairs publication "The social situation in the European Union 2003". 43 See Wallace, C., Haerpfer, C., Mateeva, L. (Institute for Advanced Studies, Vienna) "Health and Health Care Systems in the Applicant Countries", August 2002, p. 8. 44 Social Protection System in the 13 candidate countries – A Report to the European Commission, DG Employment and Social Affairs – november 2002. 23 Section 1 The social situation in brief tematic assessment of medical technologies and treatments would help to ensure that increased expenditure is only a result of genuine progress and that opportunities for savings are not missed. Such assessment – and dissemination and implementation of the results – is crucial for the three goals of access, quality and viability. However, monitoring progress at present is very dependent on the quality of the data related to health. Important weaknesses can still be observed at EU level, both in terms of data availability and standardisation of definitions and data collection methods. …and the ageing of medical personnel. The problems with recruitment and retention of medical personnel, which are already being felt in some Member States, are likely to be accentuated by the overall trend towards an ageing and shrinking workforce in this sector, resulting in the competition for manpower becoming tougher. Both trends could increase costs. Thus, the health sector will have to adjust to the impact of ageing on its personnel as well as on its clientele. This is particularly true for nurses: In seven Member States 40% of nurses are already more than 45 years of age and in another five Member States almost one in two nurses have reached this age. Two other factors contribute markedly to the shortages of nurses: 'Stop-go' trends in recruiting policies and most importantly: demanding working conditions in combination with moderate pay leading to a high staff turnover. The recruitment of immigrants to fill shortages in this sector is likely to grow in importance. Information and communication technologies (ICT) have been introduced into health systems as with most of the other parts of the economy. They can substantially improve the organisation of health care delivery. Some health care authorities indicate that they are currently spending 20% of their capital equipment budget on ICT. Generalisation of ICT may create new barriers for disadvantaged groups to get access to high quality health care if it requires patients to have certain digital skills. Enlargement may raise new challenges in relation to personnel. When the freedom of movement applies fully to the acceding States it may impose further challenges to the provision of treatment and services in these countries. This may be from people seeking medical treatment in other Member States and also from medical staff being attracted by higher wages in the current EU countries. ...population ageing... As a result of sustained low birth rates and increasing life expectancy, Europe's population is ageing. The first baby-boomer cohorts will be retiring in the next ten to fifteen years, leading initially to increased expenditure on pensions. Ten years later as these cohorts begin to move into the fourth age, their sheer numbers are likely to result in a higher need for health and – in particular – long-term care provisions. However, the need for care will, to a certain extent, depend on the effectiveness of previous and future health promotion strategies. In response the healthcare sector will need to undergo a process of perpetual transformation and develop better synergies with other policy areas. The impact of demographic ageing on future health costs is difficult to predict45. It relates to both the demand for, and supply of, health care and it is clearly linked to living conditions, lifestyles, family support and the socio-economic situation. For health care, the most important demographic trend is the growing number of very old people (over 80 years old), in a context where households are reducing in size and families may be less able or willing to respond to care needs. On the one hand health care systems will have to adjust to the changes in the pattern of illness and care needs, with geriatric medicine and care for chronicle diseases being expanded and upgraded in importance. On the other hand formal health care systems will have to prepare for a situation where they may have to handle a substantially larger share of care needs as in many Member States the role of families in care provision shrinks. Moreover, while the share of the very old in need of long term care may fall as a consequence of better health and less disability the absolute number is still likely to increase. The combined effect of technological progress, rising incomes and expectations and population ageing will create a structural trend towards rising health expenditure. Hence, a key challenge in future health policy will be to make health services so effective and cost-efficient that wide access to high quality health and long term care becomes fully sustainable, even when faced with these trends. This calls for determined efforts towards better governance and impact assessment in relation to health interventions, treatments and technologies. Ageing will lead to greater pressures on health care services and long term care provision. Adapting to sudden changes in the pattern of pathologies and while meeting manpower needs and ensuring sustainability, quality and accessibility in the long term present policy makers and administrators with a complex mix of challenges. As previously discussed, strong links between socioeconomic factors (namely education level, family patterns, gender inequalities, income and employment) 45 Projections based on the Eurostat baseline demographic scenario suggest that, on average within the EU, the volume of total health expenses could increase ceteris paribus by almost 0.6% per year in real terms as a result of the changes in population age structure over the next quarter of century. Moreover the Economic Policy Committee has estimated that the ageing induced growth in public expenditure on health and long-term care from 2000-2050 could amount to 2-3 percentage points of GDP. However these projections should be treated with caution since they refer to very long periods and rely on several assumptions about future economic and behavioural trends. 24 The social situation in brief Section 1 and health are found in all Member-States and inequalities in health status are still substantial. While not wholly unrelated to the character of health care systems these inequalities are primarily linked to the wider societal inequalities reflected in the socio-economic determinants of health. On that basis it could be argued that policies, which promote employment, improve the quality of jobs or lower inequalities, could lead to significant improvements in the health situation of the population. Indeed, one of the findings of this report is that, in addition to health policy, social and employment policies in combination with economic policies can make significant contributions to the creation and maintenance of good health. Hence, another major challenge will be to better exploit the synergies between health policies and those policies affecting the socio-economic and environmental determinants of health in order to ensure good healthy living conditions for all Europeans throughout all the stages of their lifecycle46. 46 The Commission Communication on Impact Assessment (COM(2002) 276 final) is relevant to this discussion. 25 Section 1 The social situation in brief 1.3. The resilience of the European Social Model In 1993 when the European Council in Copenhagen asked why the Union's growth potential, competitiveness and employment was lagging behind other major economic areas several voices suggested that the poorer performance resulted from fundamental weaknesses in the existing European model of society. Others contended that the basic tenets of the European model of society would be fully compatible with efforts to substantially improve the Union's overall performance. A decade later, indicators collected for the Report on "The Social Situation in the European Union" seem to validate that the Union and its Member States decided to continue an approach aimed at preserving solidarity and social cohesion47. dimension. On the one hand the sector contributes to the quality of life and better health translates into better economic performance (higher productivity, less absence, lower need for health care etc.). On the other its development is a driver for employment growth. More than 2 million jobs or 18% of the total job-creation between 1995-2001 happened in the health and social work sector, which now accounts for almost 10% of total employment. As highlighted in this year's synthesis report48 those Member States that perform best on all crucial indicators are those where the principles of active welfare states are applied with the greatest consistence and commitment. The performance of these Member States demonstrate that there is a potential for further progress which needs to be better tapped in coming years. The European Employment Strategy and the new processes on modernisation of social protection and promotion of social inclusion are organised to enable all Member States to draw on the common fund of knowledge about how Europe can move further towards economic and social sustainability. Indicators for employment, education, health and general well-being found across this report generally confirm that substantial progress has been achieved and that Europe is as capable of delivering good living conditions for the wide majority of its citizens as other major economies. Over the last decade employment promotion and modernisation of social protection have increasingly become key priorities at the heart of the overall strategy of the Union. Employment and social policies have undergone rapid development in Member States and a process of catching up and convergence has taken place. As a result we have witnessed not the withering away of European approaches built on a combination of market dynamics and public efforts, but a strengthening and further development of the European Social Model. Of course considerable problems persist and the challenges for the Union are likely to be even greater in the coming decade than they were in the previous one. For example, there are still concerns about the trends regarding the young generation as underlined in several parts of the Social Situation Report: persistent unemployment, specific mortality and work related accident rates and lack of professional education. The persistence of poverty-traps is another matter for concern. However the way forward, as shown by the best performing Member States, still lies in the improvement and modernisation of the functioning of the European Social Model. It is now generally recognised that quality social policies geared to support employment can enhance economic performance. The health sector is a good example of this synergy between the social and the economic 47 Growth, competitiveness, employment, - The challenges and ways forward into the 21st century; Commission, 1993. 48 "Choosing to grow: Knowledge, innovation and jobs in a cohesive society" Report to the Spring European Council, 21 March 2003 on the Lisbon strategy of economic, social and environmental renewal, COM(2003) 5 final. 26 The social dimension of health Section 2 Section 2 The social dimension of health 27 The social dimension of health Section 2 2.1 Health trends of the European population ● The health of EU citizens has improved greatly, as reflected by the evolution of mortality and morbidity trends. The EU population is characterised by low mortality and high life expectancy at birth. The latter indicator has increased by eight years for both sexes over the last forty years. Although life expectancy is six years higher for women than men, due to persistently higher male mortality throughout the entire life cycle, the gap is starting to narrow as life expectancy has increased more for men than women in the last decade in the majority of the Member States. ● Mortality is increasingly concentrated in the elderly and, as infant mortality is currently very low, further increases in life expectancy are now dependent on reducing mortality amongst the elderly through prolonging longevity. ● There are two exceptions to this general trend of mortality rates increasing with age: infant mortality and mortality of young people. Achieving further reductions in the levels of infant mortality and the mortality of young people can still be seen as challenges for public health: – Even in developed societies the first year of life is still a period of specific mortality risk, reflected by infant mortality levels. These have decreased in recent decades in all the Member States, which currently present levels that are among the lowest in the world. However, the persistence of differences in the existing infant mortality levels between social groups or territories demonstrates that further improvements can still be achieved. – Health improvement among young people has not followed the same pace as that of society in general. Young people, and young men in particular, presently face relatively high death rates that are linked with risky behaviour and lifestyles. Drug abuse, including alcohol, is frequently the source behind the excessive number of young people's deaths from external causes: mainly car accidents but also other types of violent deaths, such as suicides. ● As mortality is progressively concentrated in the elderly, degenerative and chronic diseases are growing in importance as causes of death. The most common causes of death are diseases of the circulatory system (around 40% of all deaths), cancer (a quarter of all deaths), diseases of the respiratory system, digestive diseases and deaths due to external causes of injury and poisoning, including car accidents. However, this general pattern varies by sex and, especially, by age. ● Morbidity is also increasingly concentrated within the elderly. Available evidence shows that mental (neuro-psychiatric) disorders, injuries, cardiovascular diseases, musculoskeletal diseases and cancer are the major causes of years of life spent with disability. ● As a result of increasing life expectancy, combined with changes in fertility, the EU population is becoming increasingly older. This demographic ageing means that the number of older people is growing while the share of those of working-age (15 to 64) will decrease. These demographic trends will have economic and social consequences in a number of areas, including healthcare systems, as mortality and morbidity shift towards older ages. ● The effect of demographic ageing on the future cost of healthcare has become a focus for debate. However, the number of older people is only one of several major drivers of this future cost, which are related to both the demand for, and supply of, healthcare. The resulting combination of demand and supply factors is difficult to predict and projections should be treated with caution. For the provision of health care the most important demographic trend is the increasing size of the over 80 years age group, in a context where households are getting smaller and families are less able to provide the increased levels of care required. ● Although health standards are currently improving in the acceding States and candidate countries, they are generally lower than those in the EU Member States. However, large health differences are observed among the acceding States and candidate countries, with Cyprus and Malta reporting health standards comparable to the Mediterranean Member States. Mortality and infant mortality are higher whereas life expectancy is lower, with a higher incidence of non-infectious diseases (especially heart disease, diseases of the circulatory system and cancer), infectious diseases and violent deaths. However, present transformations in the age structure (ageing) as well as in household structures means that acceding States and candidate countries will face similar demographic challenges regarding health and healthcare as those experienced in existing Member States. 29 Section 2 The social dimension of health Introduction most Member States. In future, households will be smaller and in turn, families will be less able to provide the increasing levels of care required, making the role of both formal and informal carers much more important. These effects will be particularly exacerbated when the post-war baby-boom age cohorts reach the age of high dependency as their own fertility was significantly lower than that of their parents. Population trends are core elements of health developments. Therefore, this presentation of data and issues on health begins with an analysis of the health implications of EU demographic trends. The ageing of the European population is expected to result in growing needs for health and long-term care services. Such expectations are based on two developments. Firstly there is an increasing number (in absolute and relative terms) of people reaching old and very old ages. Secondly, mortality and morbidity are shifting towards these older age groups. 2.1.1. … and there is a mortality and morbidity shift towards older ages. Within the broad framework of the demographic change, the 'epidemiological transition' model was established in the 1970s as a way to explain variations in mortality trends1. Earlier mortality patterns, characterised by high infant mortality and a strong presence of infectious diseases had been replaced by new patterns, where mortality becomes increasingly concentrated in higher age cohorts and where cancers and circulatory related diseases become the main causes of death. The impact of population dynamics on health The demographic trend and its implications: the EU population is increasingly older… The EU population is becoming increasingly older. Growing life expectancy combined with changes in fertility indicate that ageing will become even more pronounced in Member States in forthcoming decades, as post-war baby boomers will reach the age of retirement (from 2010 onwards). Eurostat baseline scenarios show that the number of people aged 65 and over are expected to increase by 25 million between 2010 and 2030 (a relative growth of 36%), whereas the population aged under 50 will decrease. This trend will continue until the mid-2040s, when the share of older people will start decreasing, as baby-boom cohorts will be replaced by more recent generations, which are fewer in number. This demographic trend will have economic and social consequences in a number of areas, with important policy implications: in employment and labour markets, in pension systems and in healthcare systems. According to this epidemiological transition model, the improvement of mortality levels is a result of a complex series of factors linked to social modernisation. The most relevant factors for the European Union appear to be social and economic progress, linked to an increase in quality of life, followed by scientific, medical and health care improvements. Following the epidemiological transition model, the 'health transition' model was introduced in the mid1980s2. This health transition model examines the factors behind the evolution in health status using environmental, biological, social, cultural and economic changes to explain past mortality and morbidity trends, and to describe current health-status situations and their possible future evolution. This framework of analysis places the change in EU mortality and morbidity trends within the process of a shift in prevalence from infectious diseases to degenerative and chronic ones, which are progressively concentrated in the elderly3. Within this context, the future evolution of population age structures, and the resulting increase in the number of elderly people, can be seen as a challenge for the future of European care systems and the health of their populations. For the provision of healthcare the most important demographic trend is the increasing size of the over-80 group. This age group will increase by 8 million between 2010 and 2030, an increase of 44%, which is a growth rate that is higher than that experienced by the other older population cohort groups in general. This trend outlines an additional challenge: at present, the majority of people in the over-80 cohort who need permanent assistance and care are attended to at home by their families, while the ratio being looked after by professional service providers is still rather low - and the latter are largely outside the national health system in 1 2 3 This chapter will focus on the current characteristics of mortality and morbidity in the European Union, followed by some reflections on the impact of demographic ageing on healthcare costs. A. R. Omram (1971): "The epidemiologic transition: a theory of the epidemiology of population change", Milbank Men. Fund. Q. (49), pp. 509-583. The best-known formulation of this theory has been established by Frenk, among others. See for instance: J. Frenk et al. (1991) “Elements for a theory of the health transition", Health transition review (1), pp. 21-37. In industrialised countries, the process, which started in the nineteenth century, was due to changes in risk factors like the improved availability of food, public health infrastructure and the life styles of individuals. These transformations were made possible by the social and economic changes brought about through industrialisation and modernisation. On the other hand, in developing countries, where mortality levels decreased much later, it has been medical progress (vaccines, new medicines and improvements in hospital therapeutics) which has contributed to the reduction of mortality levels without affecting the level of risk in the population. 30 The social dimension of health Section 2 2.1.2 antibiotics during the Second World War. However, at the beginning of the 1960s, the benefits of these declines in infant mortality and infectious diseases were nearly exhausted. Mortality progressively shifted towards older age cohorts, with cardiovascular diseases and cancer becoming the main causes of death10. Mortality trends in the European Union The mortality of the EU population, if measured by the indicator known as the crude mortality rate4, decreased throughout the first half of the 20th century. The main reasons for this were improved living conditions, in terms of hygiene, education and food, as well as other factors such as the development of national health systems and medical and scientific progress. This falling trend was only interrupted by specific events, such as epidemics (the Spanish influenza in 1918, for instance) and the two World Wars. As a consequence of these new patterns, life expectancy rates started to grow at a slower pace after 1960 and with marked differences between eastern and western Europe. While cardiovascular related deaths have decreased in all western European countries, improving life expectancy in the European Union, they increased in central and eastern Europe from 1965 to 1985. Political and economic transition also had a serious impact in central and eastern countries in the early 1990s, increasing mortality (especially violent deaths, including suicides) and decreasing life expectancy. Consequently, life expectancy at birth is currently higher in EU Member States, where the national figures are between 73 and 78 years for men, and between 79 and 83 for women, than in central and eastern European acceding States and candidate countries, where values for men are between 65 and 72, and for women between 75 and 78 years 11. Furthermore, the values are much lower in other eastern European countries like Russia, Ukraine, etc. However, crude mortality was more stable in the second half of the 20th century, with rates fluctuating around 10 deaths per 1,000 inhabitants. This stability (or even an increase in several Member States) in a context of growing longevity is mainly due to the ageing process: this indicator is affected by the changing age structure of the population5. Therefore, other indicators, which use standardised age structures, like standardised mortality rates or life expectancy, are better indicators of mortality trends. Life expectancy at birth is still increasing but at a lower pace In 2000 the average life expectancy at birth for the EU15 was 78 (75 for men and 81 for women). This is higher than in the US (74 for men, 80 years for women) but lower than in Japan (78 years for men, 84 for women)6. The current figure represents an increase of 33 years during the 20th century from an estimated average life expectancy of 45 years in 19007. In 1960 the life expectancy of the EU-15 had already reached 70 (67 for men and 73 for women). Therefore, a life expectancy increase of 25 years was achieved in the first 60 years of the century, followed by a gain of only 8.2 years in the last four decades8 (7.9 for men, 8.5 for women). Male life expectancy reached 68 years in 1970, 71 in 1980, 73 in 19909 and finally 75 years in 2000. In the same period, female life expectancy was 75 years in 1970, 77 in 1980, 79 in 1990, reaching 81 in 2000. Graph 1 Life expectancy at birth by sex, 2001 90 90 Men 85 83 83 83 Women 85 82 82 81 81 81 81 81 81 81 80 80 80 79 78 77 76 76 75 75 75 75 75 75 75 75 76 79 80 76 74 74 73 75 70 70 65 65 60 60 F I E S FIN EU15 L A B EL D NL UK P DK IRL Note: EU-15, B, L, A data from 2000; D data from 1999 Source: Eurostat Before the 1950s, the fast growth in life expectancy at birth was mainly due to the reduction in infant mortality and infectious diseases. In a context of improving living conditions, this considerable progress was accelerated by, among other factors, the diffusion of vaccines, the discovery of sulphonamides between the wars and Today, as mortality affecting the young remains very low in the EU, further increases in life expectancy will be increasingly dependent on our ability to prolong the length of life for the elderly and reduce avoidable deaths (such as road traffic accidents). 4 5 6 7 8 For a given territory, this is calculated using the number of deaths in a period divided by the average total number of inhabitants during this period. Ageing implies a greater number of elderly people, at a time when mortality is more concentrated in the elderly. Source: Eurostat NewCronos database. Average of 43 European countries. Source: J. Vallin, F. Meslé (2001) “Trends in mortality and differential mortality”. Council of Europe, Strasbourg. The nature of the indicator partly explains this slow-down. For a given year, life expectancy is the average age that a new-born baby may expect to reach if the mortality rates of this given year were maintained. As the total number of years of life lost by a person who dies in the first year of life is much higher than the years lost by a person who dies, for instance, at 65, life expectancy is more sensitive to the reduction of infant mortality than to increasing longevity at older ages. 9 However, the increase in life expectancy stopped during the second half of the 1980s and early 1990s in some southern Member States for men as a consequence of the increase of mortality caused by AIDS and traffic accidents affecting young men. A similar trend can be observed for women in some Nordic Member States. Evidence found for Denmark shows that lung cancer, linked with high female tobacco consumption, is one of the causes of the relatively low life expectancy of Danish women. 10 Source: J. Vallin, F. Meslé (2001): “Trends in mortality and differential mortality” (Council of Europe). 11 Source: Eurostat NewCronos database. 31 Section 2 The social dimension of health Characteristics of mortality in the EU Member States Young people represent another age group where mortality characteristics have changed in recent years. However, for this age group, the changes have not been positive due to specific causes of death affecting the young, and young men in particular, which are linked to behaviour. Therefore, reductions in their incidence is more dependent on lifestyle changes than on medical progress. In fact, accidents, poisoning and violence – all external causes – are the leading causes of death amongst young people (aged 15 to 24) in all Member States. Examining this trend in more detail, motor vehicle accidents represent the majority of accidental deaths, with marked country and gender differences: male rates are much higher than female ones. This is also the case for suicides, where male rates are three times higher than female ones. Furthermore, between Member States, suicide rates vary by a factor of about 10 in both genders, with minimum values found in Greece and the maximum in Finland13. However, it is worth noting that, for cultural reasons, suicides may be under-reported in some Member States. Death risks, and therefore the level of mortality, are dependent on age, sex, marital status and place of residence, among other factors. These variations in differential mortality, as well as trends by cause of death, are detailed below. Mortality trends by age. Progress in reducing mortality has been particularly significant in the very young, as shown by the infant mortality rate12. This indicator is currently at a very low level, having fallen throughout the 20th century, mainly due to a reduction in exogenous mortality, especially infectious deaths linked to social, economic and medical changes – for example better food, the diffusion of health prevention policies (better daily health practices), and scientific and medical progress (new vaccines and medicines). per 1,000 births Graph 2 Recent studies from Finland investigating these trends suggest that substance abuse, including alcohol, is often a common denominator behind the deaths of young people from external causes and suicides. This underlines the fact that a change of behaviour is needed if the incidence of these causes of deaths is to be reduced. Infant mortality rate, EU-15. 1960-2001 40 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 However, these recent trends in youth mortality are the exception to the general pattern of delaying death and increasing longevity in the EU. As mortality is increasingly concentrated in the older age groups, more individual characteristics, linked to lifestyle and biological factors, and not just traditional economic and social factors, are influencing longevity. It is possible that biological and lifestyle factors could explain, at least in part, the high longevity in southern Member States14. However, more evidence is needed to explain variations in life expectancy in very old ages and to highlight the factors influencing longevity. 0 0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 Source: Eurostat. Although infant mortality continues to decrease in the Member States, it does so at a slower pace. There are two main reasons for this. Firstly, the current very low level makes further improvements more difficult. Secondly, at present most infant mortality is not due to external factors, but to internal ones, such as congenital problems, which are more difficult to eradicate. However, progress in medical treatment in obstetrics and neonatology, for instance in cases of premature births, is decreasing the incidence of this type of mortality. Moreover, the persistence of differences in current infant mortality levels among social groups or territories demonstrates that further improvements can be achieved if health policies focused on groups at risk are implemented. In this sense, the infant mortality rate can be considered to be a good proxy of existing inequalities within a population. Mortality trends for the different age groups are illustrated in the graph below, which shows current mortality rates by age in the EU for men and women. As explained, mortality rates generally increase with age. However, even in developed countries the first year of life continues to be a period of relative risk. Male rates increase more rapidly than female rates, as they are more affected by road accidents and other accidental deaths, suicides, AIDS and other diseases that could be linked with the 'male lifestyle'. This age pattern is one of the causes of lower male life expectancy, although this trend is now starting to change in several Member States, as illustrated in the following paragraphs. 12 The ratio between the number of deaths of children below the age of one, and the number of births. 13 Source: Eurostat NewCronos database. 14 For example, recent research on centenarians in several Mediterranean islands, like Crete and Sardinia, has highlighted the importance of both genetic and lifestyle factors (like healthy diet and regular exercise). For example, see Poulain, M. et al (2001) "Evidence of an exceptional longevity in the Sardinian mountanious population". European Population Conference, Helsinki, 7-9 June 2001. 32 The social dimension of health Section 2 Graph 3 100000 When analysing the main causes of deaths in the ages where male over-mortality is higher16 there is a link with certain lifestyle patterns by age. This implies greater consumption of tobacco, alcohol and other drugs, greater incidence of fatal work accidents and road accidents, resulting in a larger exposure to risk factors for men than women. Therefore, mortality inequalities by sex, although conditioned by biological factors, are mainly attributable to social causes. Probability of dying by age, EU-15, 1996 100000 per 100,000 people 10000 10000 1000 1000 Men Women 100 100 However, social factors affecting male over-mortality are not immutable. The behaviour of men and women in the EU is becoming more similar as women adopt traditionally male practices. As a consequence, male and female life expectancies, which diverged in the last century, are now beginning to converge. This has already been observed at EU-15 level (where life expectancy at birth has increased 2.5 years for men between 1990 and 2000, compared with only 2 years for women) and in the majority of the Member States. Only in Greece, Spain and Luxembourg did life expectancy increase more for women than men in the last decade, while the increases have been equal in Portugal17. 10 10 0 10 20 30 40 50 60 70 80 90 100 Source: Eurostat Graph 4 Male over-mortality: probability of dying by age for men compared to women (=1). EU-15, 1996 3,5 3,5 3,0 3,0 2,5 2,5 2,0 2,0 1,5 1,5 1,0 1,0 0,5 0,5 0,0 Infant mortality (affecting children less than 1 year old) also shows a certain level of male over-mortality. At this age, exogenous mortality (causes linked to the environment), which affects both sexes with similar intensity, is less important than endogenous mortality (related to genetic factors), which affects more male babies. Therefore, this is the only case where biological reasons appear stronger than social ones for explaining male over-mortality. 0,0 0 10 20 30 40 50 60 70 80 90 100 Source: Eurostat The gender dimension of mortality trends Mortality trends by marital status. Male ‘over-mortality’ (the gap between male and female mortality rates across age cohorts), resulting in lower life expectancy for men, is a well-known phenomenon in all Member States and in the majority of other world nations15. Moreover, this gender gap increased during the last century. Several studies have shown that married people have a longer life expectancy than the single, divorced and widowed. Some researchers maintain that the difference between the two groups extended to all countries where data is available from the 1950s up to the 1970s or early 1980s. However, if the absolute and relative figures on differential mortality are examined more closely, analysing working age and elderly people separately, the results are more complex19. Graph 4 shows that men have a higher mortality risk than women at all ages. This over-mortality is especially pronounced between the ages of 20 and 25, where men are around three times more likely to die than women. A second period of high male over-mortality occurs between the ages of 50 and 70, where men are around twice as likely to die. It is the over-mortality of men in this latter age group that is the stronger determinant of the gap between male and female life expectancy; although the over-mortality value is not as large as in the younger age group, the number of people affected is higher. ● For those between the ages of 45 and 54, data shows that the relative over-mortality of the unmarried active population has increased for both men and women, while it has decreased if absolute numbers are used, as mortality levels have gone down. There are also important differences between countries. While absolute and relative over-mortality have grown in Hungary, they have reduced in Sweden. 15 Only certain developing countries, where the social, cultural and political situation of women is especially unfavourable, display female over-mortality. Source: United Nations Population Division. 16 Cardiovascular diseases and cancer among the 50-70 year olds and accidents among young men. 17 Source: Eurostat NewCronos database. 18 Source: Y. Hu, N. Goldman (1990): “Mortality differentials by marital status: An international comparison”. In Demography, 27 (2), pages 233-250. 19 See T. Valkonen (2001) “Trends in mortality and differential mortality” Strasbourg, Council of Europe. 33 Section 2 The social dimension of health ● When differential mortality by marital status of people aged 65-74 is analysed, absolute and relative overmortality of unmarried people have both increased, especially amongst women (in all countries except Poland and Greece). Graph 5 Mortality rate caused by diseases of the circulatory system per sex, 1999 500 per 100,000 people Women 450 430 400 414 368 328 285 300 250 207 300 257 208 219 203 188 200 350 282 234 220 349 314 282 277 400 367 358 321 250 409 394 388 374 350 Therefore, the protective effect of marriage, or the opposite effect for unmarried people, appears to have grown, although with some exceptions. However, Valkonen argues that there is not a clear explanation to this trend: it is improbable that it is simply due to the negative selection effect for single people, as the over-mortality can also be seen in the other unmarried statuses. The important role of social networks (and specifically the weaker social networks of unmarried people) could partly explain these differences. Indeed, some evidence to support this has been found for Finland, which will be discussed in section 2.4. However, it is clear that more studies are needed before this trend can be clarified. 250 223 207 210 185 200 136 150 150 100 100 50 50 0 B DK D EL E F IRL I L NL A P FIN S 0 UK EU 15 Note: B: 1995; DK: 1996; FI: 1997; E, F, IRL, I, S, UK, EU:1998 Source: Eurostat Graph 6 350 Mortality trends by major cause of death. 300 Mortality rate caused by malignant neoplasmas per sex, 1999 250 The European Union is now in the latter stages of the transition from a population with high mortality and low life expectancy towards a population with low mortality and high life expectancy. Here, mortality is increasingly concentrated in the elderly, with degenerative and chronic diseases growing in importance as causes of death. In addition to this trend, deaths resulting from accidents and other societal20 diseases, although not very significant in absolute terms, cause a decrease in the number of remaining life-years and therefore a shortening of life expectancy. 350 per 100,000 people Men Women 301 300 279 268 259 270 251 243 258 256 238 232 243 217 167 162 155 200 193 174 150 250 244 208 201 200 147 115 132 126 140 135 138 122 113 141 150 122 100 100 50 50 0 0 B DK D EL E F IRL I L NL A P FIN S UK EU 15 Note: B: 1995; DK: 1996; FI: 1997; E, F, IRL, I, S, UK, EU:1998 Source: Eurostat much higher levels of mortality by cardiovascular diseases in central and eastern countries compared with the EU Member States23. Health statistics on the main causes of death within the EU21 reveal the following. ● 500 Men 450 The most common causes of death are diseases of the circulatory system (especially heart attacks and strokes), accounting for over 1.5 million deaths in the EU each year. These represented approximately 42% of all deaths in 1998 – 45% for women, 38% for men. It is the main cause of death for women in all 15 EU Member States and the same for men in all countries except France22. However, this cause of death shows a regressive trend: the standardised death rate for this cause has decreased by 12% between 1994 and 1999 for both sexes, with a larger reduction for cerebrovascular disease (strokes) than for ischaemic heart disease. Within Europe, a clear East-West gap exists, with ● The second most common cause of death is cancer, which accounts for around a quarter of all deaths – 29% for men, 23% for women. Although its relative share has increased since 1980, in absolute terms this cause of death also has a regressive trend in the EU (a reduction of 7% for men and 6% for women) when the 1994 and 1999 standardised death rates are compared24. This decrease is even more important for cancers of the stomach (19% reduction), uterus (13% reduction), bladder (12% reduction) and breast (9% reduction). The death rate corresponding to the group of cancer of larynx and trachea, bronchus and lung has also decreased by 9% between 1994-98 for men, but has increased by 5% for 20 The societal or "man-made" diseases imply premature deaths caused by specific social behaviours or habits related to tobacco, alcohol and drugs consumption as well as mortality caused by road accidents or AIDS (as there is a behavioural component in its diffusion associated with risk practices). 21 Source: Eurostat NewCronos database unless other source is mentioned. 22 For men living in EU Member States, cardiovascular disease causes between 49% (Sweden) and 29% of deaths (France) and for women between 59% (Austria) and 36% (France). Source: British Hearth Foundation – Coronary heart disease statistics. 23 Source: WHO (2001) “The European Health Report”. Geneva: WHO. 24 In contrast, cancer mortality rates are increasing in the countries of central and eastern Europe, which had lower levels three decades ago. Now the cancer mortality rates and trends are worse in these countries, and the gap is widening. Differences in lifestyles and environmental exposure are the most likely causes, and these are inevitably linked to political, social and economic inequalities. Source: L. Dobrossy (2002) “Cancer mortality in central-eastern Europe: facts behind the figures”. The Lancet Oncology, (3) 34 The social dimension of health Section 2 women. This is a consequence of the growing tobacco consumption patterns among women during recent decades. However this type of cancer still affects more men (most common cause of death by cancer and 8% of all deaths) than women (2% of all deaths), where breast cancer is the main cancer-related cause of death (4%). Cancer of the prostate causes 3% of all male deaths, followed by cancers of the colon and stomach, as well as leukaemia, with around 2% of all deaths each. Graph 8 Mortality rate caused by diseases of the digestive system per sex, 1999 60 Men 50 50 45 43 44 43 40 40 60 53 48 48 46 per 100,000 people Women 40 40 34 30 30 28 26 25 24 23 22 29 30 24 22 22 21 23 22 25 26 24 21 20 20 16 Graph 7 180 Mortality rate caused by diseases of the respiratory system per sex, 1999 10 Men 160 160 153 DK D EL E 100 94 90 92 90 88 87 Graph 9 80 66 65 62 44 40 28 39 29 61 60 60 NL A P FIN S 0 UK EU 15 42 51 49 48 40 40 32 30 23 Mortality rate caused by accidents per sex, 1999 60 80 40 Men per 100,000 people Women 80 69 23 20 20 60 0 0 B DK D EL E F IRL I L NL A P FIN S 60 54 52 UK EU-15 46 Note: B: 1995; DK: 1996; FI: 1997; E, F, IRL, I, S, UK, EU:1998 Source: Eurostat 45 45 43 20 The third largest cause of death, diseases of the respiratory system, has a much smaller influence - 9% of all deaths - with a slightly higher share for men than for women. However, their impact is increasing: the standardised mortality rate for this cause of death increased by 8% between 1994 and 1999 for women, although it is more stable for men. 43 39 40 42 38 37 21 40 29 28 ● L 100 80 ● IRL I 120 103 ● F Note: B: 1995; DK: 1996; FI: 1997; E, F, IRL, I, S, UK, EU:1998 Source: Eurostat 140 134 133 120 114 40 B Women 140 10 0 180 per 100,000 people 100 12 26 23 22 16 12 18 17 16 14 23 22 16 15 12 12 12 20 11 0 0 B DK D EL E F IRL I L NL A P FIN S UK EU 15 Note: B: 1995; DK: 1996; FI: 1997; E, F, IRL, I, S, UK, EU:1998 Source: Eurostat rent trends. The number of deaths caused by tuberculosis and by AIDS decreased sharply between 1994 and 1999 as well as their corresponding standardised death rates, whereas death rates caused by viral hepatitis have more than doubled for men and more than tripled for women. The following causes of death each account for around 5% of deaths. They are those linked to digestive diseases (fourth cause for women: 4.3% of all female deaths, fifth for men: 4.6% of all male deaths) and external causes of injury and poisoning (fourth cause for men: 6.3% of all male deaths, but only 3.6% of all female deaths), which includes transport accidents, suicides and homicides. Both causes of deaths have decreased in the period 1994-99, as shown by the standardised death rates: death from digestive diseases decreased by 9% for men and 7% for women whereas violent deaths experienced a reduction of 9% for men and 10% for women. The incidence of deaths caused by diseases of the digestive system and the incidence of deaths caused by accidents are illustrated in the graphs below. Mortality patterns by cause vary depending not only on gender, but also by age. The remaining causes of death are less significant. For instance, infectious and parasitic diseases, which were an important mortality cause several decades ago, represented less than 2% of all the deaths in the EU in 1998 and with a clear regressive trend. However, within this group there are diseases with very diffe- ● Perinatal problems25 and congenital malformations are the main causes of death during the first year of life. ● Between the ages of 15 and 39 external causes (especially road accidents) are the predominant causes of death, followed by diseases related to AIDS26 and cancers. ● Cancer is the main cause of death between the ages of 40 and 69, followed by circulatory diseases. ● Finally, the diseases of the circulatory system, which are linked to chronic and degenerative processes, followed by cancer and respiratory diseases, are the main cause of death from 70 years onwards. 25 Perinatal mortality includes late foetal mortality plus mortality of children within the first week. 26 Although AIDS has experienced a sharp decrease recently, it is still an important cause of death among 25-49 year olds. More concretely, over a quarter of all deaths caused by AIDS are in the 30-34 age group. 35 Section 2 The social dimension of health Graph 10 Main causes of death by age, men. EU-15, 1998 100 100 Other (included ill-defined causes) 80 80 Diseases of the digestive system 60 60 Map 1 > 76 75 - 76 74 - 76 <= 74 Data not available Diseases of the respiratory system IRL: National level DED, UKM (Scotland): NUTS 1 D, UKM: figures based on 1995 national and regional population scenarios. F: 1997; I: 1997-1998 External causes 40 Life expectancy for men at birth in the EU countries in 1997-1999 (3year average) 1999, NUTS 2 40 Neoplasms (cancer) 20 0 20 0 5 15 25 35 45 55 65 75 0 85+ Diseases of the circulatory system Congenital anomalies Source: Eurostat - NewCronos Graph 11 Main causes of death by age, women. EU-15, 1998 100 100 Other (included ill-defined causes) 80 80 Diseases of the digestive system 60 60 40 40 20 20 Diseases of the respiratory system External causes Neoplasms (cancer) 0 0 0 5 15 25 35 45 55 65 75 Statistical data: Eurostat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 12/2002 Diseases of the circulatory system Congenital anomalies Map 2 85+ Source: Eurostat - NewCronos These patterns can be seen in the following graphs where the share of the main causes of death by age is shown for both sexes. They provide a picture of the relative importance of each cause of death through the life span, but not of the absolute numbers of deaths. For instance, more people die from cancer at the age of 20 than at the age of 5; however, the relative share of mortality from cancer is lower at 20 years old as there is a larger absolute number of deaths at that age. Life expectancy for women at birth in the EU countries in 1997-1999 (3year average) 1999, NUTS 2 > 82 81 - 82 80 - 81 <= 80 Data not available IRL: National level DED, UKM (Scotland): NUTS 1 D, UKM: figures based on 1995 national and regional population scenarios. F: 1997; I: 1997-1998 Regional disparities in mortality When analysing regional differentials in life expectancy, similar trends appear for both sexes in most countries. In other words, men and women both have a high or low life expectancy in the same regions27. However, in certain Member States regional disparity can be more pronounced for one sex, while in other countries regional variations are similar for both sexes. The maps below show some trends in regional mortality within the Member States and accession States for both sexes28. For instance, populations in northern regions of France have a lower life expectancy than those in southern regions, and the same pattern appears in the UK. This Statistical data: Eurostat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 12/2002 27 See T. Valkonen (2001) “Trends in mortality and differential mortality” (Strasbourg, Council of Europe) who has analysed regional differentials in life expectancy using data from eight Member States and three central and eastern European countries in the period from the 1970’s to the 1990’s. 28 Source: Eurostat NewCronos database. 36 The social dimension of health Section 2 Map 3 Life expectancy for men at birth in the accession States in 1997-1999. Men. (3year average) 1999, NUTS 2 Map 4 > 71 68 - 71 66 - 68 <= 66 Data not available Life expectancy for men at birth in the accession States in 1997-1999. Women. (3year average) 1999, NUTS 2 > 78 76 - 78 74 - 76 <= 74 Data not available PL, SK: National level PL, SK: National level Statistical data: Eurostat Database: REGIO. Cartography: Eurostat - GISCO, 12/2002 Statistical data: Eurostat Database: REGIO. Cartography: Eurostat - GISCO, 12/2002 north/south divide also appears in Finland, Sweden (at least for women), and Germany, where the highest life expectancy is also found in southern regions, while an opposite north/south divide, with lower life expectancy in southern regions, is found in Belgium (higher life expectancy in Flanders than in Wallonia), Italy (for women) and Spain (for women). southern Italy, southern France, southern Britain, the majority of Portugal and Greece, and some interior regions of Spain. For women, the highest levels of mortality caused by cancer are found in Denmark, Ireland and several regions of the UK (mainly in the north of England, Scotland and Wales), while the lower rates correspond to the majority of the regions in Portugal, Spain and Greece, southern France, southern Italy and northern Finland. However, it is not unexpected that the geographical distribution of cancer is different for men and women because there are very diverse types of cancer, some of which affect only one of the sexes and others with very different incidence among men and women. These geographical differences can be explained using the distribution of the main causes of death. Observing the following maps, which show the regional distribution of death rates from diseases of the circulatory system – the main cause of mortality – a higher incidence for men and a similar regional distribution for both sexes can be seen. Higher death rates caused by cardiovascular diseases are found in regions of eastern Germany and Austria, northern Britain, Ireland and Sweden, plus some regions of Portugal and Greece, whereas lower levels can be found in France (except the north) and central Spain, plus several Italian regions, mainly in the central and northern part of the country. In general, since the 1960s these regional life expectancy trends by gender have been very stable in all countries, despite considerable changes in the overall level. However, there are some disparities within these trends. Out of the eleven countries that were analysed by Valkonen29, regional gaps reduced for both men and women in six countries (Finland, Sweden, France, Italy, Romania and Russia). They increased for both men and women in two countries (Spain30 and Poland) and remained the same in the case of men but grew for women in another two (Austria and Denmark)31. Differences are more significant in the gender distribution of cancer deaths, the second highest cause of death. In the case of men, mortality levels are higher in northern France, northern Britain, north-east Germany and north-east Italy, and lower in Sweden and Finland, 29 See T. Valkonen (2001): “Trends in mortality and differential mortality” (Council of Europe, Strasbourg). 30 In Spain, regional diversity grew for both men and women in the 1970’s, before reducing in the 1980’s. 31 In the case of Austria, female regional diversity doubled, this fact is mainly due to the reduction of female mortality in the region of Vienna. In Denmark, there is a contrast between Copenhagen and the rest of the country. 37 Death rates from diseases of the circulatory system, Males. 1997/1999 - NUTS 2 Standardised death rates Map 6 Death rates from diseases of the circulatory system, Females. 1997/1999 - NUTS 2 Standardised death rates > 400 > 250 350 - 400 200 - 250 300 - 350 175 - 200 250 - 300 150 - 175 <= 250 <= 150 Data not available D, UKM (Scotland): NUTS 1 B, DK, EL: average 1994 - 1996 Data not available D, UKM (Scotland): NUTS 1 B, DK, EL: average 1994 - 1996 38 Statistical data: Eurstat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 01/2003 Statistical data: Eurstat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 01/2003 Section 2 The social dimension of health Map 5 Map 7 Death rates from malignant neoplasms, Males. 1997/1999 - NUTS 2 Standardised death rates Map 8 Death rates from malignant neoplasms, Females. 1997/1999 - NUTS 2 Standardised death rates > 300 > 170 260 - 300 150 - 170 240 - 260 125 - 150 200 - 240 110 - 150 <= 200 <= 110 Data not available D, UKM (Scotland): NUTS 1 B, DK, EL: average 1994 - 1996 Data not available D, UKM (Scotland): NUTS 1 B, DK, EL: average 1994 - 1996 39 Statistical data: Eurstat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 01/2003 The social dimension of health Section 2 Statistical data: Eurstat Database REGIO. © EuroGeographics, for the administrative boundaries. Cartography: Eurostat GISCO, 01/2003 Section 2 The social dimension of health It is interesting to compare life expectancy in urban and rural areas. However, this has only been possible in the five countries where suitable data is available32: Russia, Romania, Finland, Poland and East Germany. There was a clear divide in the results between the two poorest countries and the others. In Russia and Romania, rural areas have a lower life expectancy than urban ones, a situation that has not changed in the last three decades, while in the other countries the level of mortality in rural and urban areas is virtually the same. Future mortality trends. There are two opposing views on the future evolution of mortality and the biological limit to life. 'Optimistic' researchers back expansive theories predicting an endless growth in life expectancy, whereas more 'pessimistic' researchers defend the existence of an unsurpassable biological threshold. The first school of theorists base their arguments on scientific progress: within the context of significant discoveries in areas such as biology and genetic engineering, it is possible that there is still potential for substantial increases in human life expectancy. In fact, most previous forecasts have underestimated the fall in mortality in older age brackets and the increase of life expectancy. Following this argument, current forecasts of life expectancy could be considered to be too low. However, this optimistic picture could obviously be negatively influenced by several factors, linked to environmental and nutritional risks as well as to changes in behaviour patterns. For instance, changing trends in the rates of both taking-up and giving-up smoking, for both men and women, may result in female smokers outnumbering male smokers in several years’ time in a number of Member States. Indeed, in Denmark, currently more women than men smoke in the younger age groups. All these changes will have consequences for mortality levels and therefore will impact adversely on life expectancy growth 33. Therefore, if unhealthy habits, such as tobacco consumption, were reduced it could bring about further reductions in mortality. Avoidable deaths There is still considerable debate about the extent to which health care has contributed to population health in the EU. This has been examined in a forthcoming study by Ellen Nolte and Martin McKee, which uses the concept of amenable mortality, defined as deaths that should not occur in the presence of effective and timely health care, to look at changing patterns of mortality in the Member States. In their report, the authors show how deaths that could be prevented were still relatively common in many countries in 1980. However, reductions in these deaths contributed substantially to the overall change in life expectancy between birth and age 75 during the 1980s. In general, the largest contribution was from falling infant mortality but in some countries reductions in deaths among the middle aged was equally or even more important. These countries were Denmark, The Netherlands, the United Kingdom, France (for men) and Sweden (for women). In contrast, during the 1990s, reductions in amenable mortality made a somewhat smaller contribution to improved life expectancy, especially in the northern European countries. However it remained important in southern Europe, especially in Portugal and Greece, where the initial death rates had been higher. 2.1.3. Morbidity in the European Union An indicator on health status: Disability-free life expectancy. These findings provide evidence that improvements in access to effective health care have had a measurable impact in many countries during the 1980s and 1990s, in particular through reductions in infant mortality and on the number of deaths among the middle aged and elderly, especially women. However, the scale of impact has, to a considerable extent, reflected the starting point. Thus, those countries where infant mortality was relatively high at the beginning of the 1980s, and which had the greatest scope for improvement, such as Greece and Portugal, unsurprisingly saw the greatest reductions in amenable mortality in infancy. In contrast, in countries where infant mortality rates were already very low by the beginning of the 1990s, such as Sweden, the scope for further improvement was small. Similarly, the scope for improvement in amenable deaths in adulthood was greatest in those countries where initial rates were highest. An indicator that uses a similar methodology to life expectancy to give information on morbidity, disability and health status is '(severe) disability-free life expectancy'. It is calculated through a life table using data on mortality and disability. The results, however, have to be interpreted cautiously as morbidity and disability are, compared with mortality, less clearly defined concepts, which focus on diverse aspects of health such as disease, functional status or perceived health. As a consequence, disability data seems to be very different from one country to another, which therefore impacts on final severe-disability-free life expectancy and disability-free life expectancy national indicators. These variations in disability degrees may express, more than actual differences in rates of disability in daily life, different linguistic or cultural meaning of disability among the Member States or diverse types or degrees of disability. 32 Source: T. Valkonen (2001) in “Trends in mortality and differential mortality” (Council of Europe, Strasbourg). 33 In a context of high female tobacco-consumption in Denmark, lung cancer contributed to a loss of 1-6 months more of life expectancy for Danish women than in other European countries. Source: K. Juel, P. Bjerregaard, M. Madsen (2000) “Mortality and life expectancy in Denmark and in other European countries. What is happening to middle-aged Danes”. In The European Journal of Public Health, (10) pages 93-100. 40 The social dimension of health Section 2 Estimations made by REVES (Réseau Esperance de Vie en Santé) using Eurostat data (including ECHP data on the disability of people who do not live in an institution) at EU level for the year 1994 show that the higher the life expectancy, the lower the proportion of severe-disabilityfree years. It would mean that, as people live longer, the share of life with (severe) disability increases more that the share without disability34. However, this conclusion is obtained from using only one year's data. What are the results when comparing a time series ? Although data on (severe) disability-free life expectancy from national sources are not fully comparable, the following trends are apparent when large series of data corresponding to different industrialised countries are aggregated. Firstly, data corresponding to the last 15 years does show a slightly rising trend in disability-free life expectancy, but less so than for life expectancy. Secondly, the analysis of severe-disability-free life expectancy data suggests that this indicator evolves in parallel with life expectancy. Therefore, the increase in life expectancy seems to be combined with a decrease in the most severe disabilities and an increase in the least severe35. Below are some trends on the main diseases using Eurostat data as well as information from DG Health and Consumer Protection and other additional sources (The source used is Eurostat: "Key data on health 2000" unless another source is mentioned). Cardiovascular diseases Diseases of the heart and circulation pose the greatest risk to life; they are the main cause of mortality in the EU Member States and also cause disability in thousands of people. For Europe as a whole, ischaemic heart disease was the leading cause of disease burden in 2000 (premature death plus non-fatal outcomes resulting from new cases of the disease), accounting for 10% of the overall burden of disease and injury, with similar proportions for both men (11%) and women (9%). The second leading cause (both sexes combined) was cerebrovascular diseases, which is substantially higher in women (8.3%) than in men (5.6%)38. In the EU alone, over eight million DALYs (Disability Adjusted Life Years) are lost due to cardiovascular diseases, of which over four million are lost due to heart disease and over 2 million are lost due to strokes39. As the risk of circulatory diseases increases with age, the evolution of the population age structure will probably accentuate absolute numbers even if relative incidence rates decrease. Comparing socio-economic groups, it seems that disadvantaged groups not only live shorter lives but they also have the highest share of years lived with disabilities. Therefore, this indicates that there is no trade-off between the quantity and the quality of years lived; rather, it would be possible for people to live both longer and in better health. The trade-off would be between the levels of disability severity rather than between longevity and disability. However, more studies are needed in this area. If premature deaths are not considered, then circulatory diseases are not one of the major causes of years of life with disability – compared with neuro-psychiatric disorders and injuries – but they are still a significant cause in the EU and especially in central and eastern Europe. In the EU alone nearly 1.4 million years of disability are due to cardiovascular diseases, of which more than half are lost due to strokes40. The main diseases affecting EU citizens. Eurostat and DG Health and Consumer Protection are working to improve the data available on morbidity36. However, currently there is a general problem in the lack of harmonised data on morbidity covering the whole EU population, with the exception of cancer and some communicable diseases. Available evidence shows that cardiovascular diseases, cancer, neuro-psychiatric disorders and musculoskeletal diseases are among the major morbidity factors37. The incidence of circulatory diseases is strongly related to levels of physical activity and diet. A diet rich in fruits and vegetables, with non-refined cereals and an appropriate amount of fatty acids, reduces the risk of suffering circulatory problems, whereas a high-cholesterol diet increases the risks, especially if it is accompanied by tobacco consumption, high blood pressure, obesity and physical inactivity41. The effect of the diet seems to 34 The same can be said about the differences between men and women. REVES data suggests that women also have more disability-free years (61.5 in 1994 at EU level) and severe disability-free years (74.3) than men (59.7 years and 69.2 years, respectively). Moreover, (severe) disabilityfree years account for a lower proportion of total life expectancy for the female population: 77% of the whole life without disabilities at EU level (16% with some disabilities and 7% with severe disability) compared with the respective shares 81%, 13% and 6% for men. 35 Source: J-M. Robine in “Can we hope for both long life and good health?”. Background paper for the "Panel on a Research Agenda and New data for an ageing world’ organised by the National Research Council, London, 16-17 September, 1999. 36 For instance, by investigating methodological issues like the effects of the different methods of obtaining data on the incidence and prevalence of diseases in the different countries. There are two basic types of morbidity statistics - those giving the incidence and those that indicate the prevalence of a disease. Incidence measures the number of new cases for a given period and population (e.g. the number of new cases of a disease per 1000 population in a year), while the prevalence indicators provide the proportion of a population with the disease at any given time in the year. 37 Cardiovascular diseases and cancer are also major causes of death, whereas neuro-psychiatric disorders and musculoskeletal diseases are not. This indicates that mortality and morbidity trends are sometimes, but not always, linked. 38 Source: World Health Organization, (2002) The European Health Report 2002. Geneva: WHO 39 The DALY or Disability-Adjusted Life Year is a measure developed to quantify the burden of disease, which takes into account years of life lost due to premature mortality and years lived with a disability of specified severity and duration. One DALY (lost) is thus one lost year of healthy life. All types of cardiovascular diseases together are the first major cause of DALYs lost in former socialist European countries, and the second, behind neuropsychiatric disorders, in western European countries. Source: British Hearth Foundation – Coronary heart disease statistics. 40 Source: British Hearth Foundation – Coronary heart disease statistics. 41 Source: Société Française de Santé Publique (2000): “Health and Human Nutrition: Element for European Action”. 41 Section 2 The social dimension of health explain the current distribution of morbidity levels due to circulatory diseases with Mediterranean countries experiencing, in general, good indicators. From EU registered data (case studies from the mid-1980s to the mid-1990s) the highest average heart attack rates are found in areas of the UK and Finland for men and in the UK for women. The lowest rates are in areas of Spain and France (men and women), Switzerland (men) and Italy (women). Graph 12 Breakdown of cancer types - Males 1997 0 5 10 15 20 Other 18.5% Leukaemias 3.0% Non-Hodgkins lymphoma 3.6% Kidney and urinary 3.8% Lip, oral cavity and pharynx 5.4% Stomach 5.6% Bladder 7.3% Colon/rectum Cancer. 14.7% Prostate 18.6% Lung Cancer incidence increases with age, reaching a maximum incidence rate at around age 70. It follows, therefore, that its impact is much stronger in developed societies with long life expectancy. Within Europe it appears that cancer morbidity prevalence is high in countries where survival is also high, and low where mortality levels are higher. 19.6% 0 5 10 15 20 Source: Eurostat Graph 13 Breakdown of cancer types - Females 1997 0 5 10 15 Other The number of new cases in 1995 for the whole EU was estimated at 1.5 million, with relative survival42 rates of European adult cancer patients estimated at around 40% for men and more than 50% for women (1985/1989 data). Pancreas 2.6% Cervix uteri 2.9% Non-Hodgkin’s lymphoma 25 30 3.1% Stomach 4.0% Ovary 4.4% Corpus uteri Although men are more affected by the illness than women in all countries, certain regional difference can be identified. The highest incidence rate for men, standardised for age, is in France and for women in Denmark. The lowest rates for both men and women are in Spain, Greece and Portugal. As for the type of cancer, lung, colon and rectal cancer register the highest incidence. Cancers affecting the lungs were the most frequent in men while breast cancer was the most common form among women. Furthermore, the cancer survival rates vary within the EU. 20 17.9% 4.9% Lung 5.7% 13.7% Colon/rectum Breast 28.4% 0 5 10 15 20 25 30 Source: Eurostat Member States since the second half of the 1980's, which is likely to be a result of advancements in survival following mammography screening and therapeutic advancements. Survival rates vary depending on whether or not the cancer is localised, or spread beyond the area of diagnosis. The rate of survival is over 90% when the cancer is contained within the breast, 75% when it has spread to adjoining areas, but below 20% when the cancer reaches more distant parts of the body. Cervical cancer is the only type of female cancer that does not show a north-south divide. Its decrease is mainly due to the success of screening programmes. Lifestyle (especially tobacco and alcohol consumption) and nutrition seem to be linked with cancer incidence. A diet rich in fruits and vegetables, combined with low alcohol consumption and no tobacco consumption, can be linked with a lower risk of having cancer of the mouth, pharynx, oesophagus, stomach and lung43. The high incidence rates of lung cancer among men are mainly due to tobacco consumption, but also to occupational and environmental exposure. The incidence in men appears to have stopped rising, although it is growing for women in southern Member States. Prostate cancer is the second most frequent cancer for men. Incidence is again higher in the north than in the south. It is possible that the increase in incidence rates is due to new ways of detecting the illness. Breast cancer is the most common type of cancer for women in the EU, with almost 30% of all new female cancer cases. However, while incidence rates are increasing in all Member States, mortality has started to decrease in younger women (20-49 years old) in most EU Incidence rates of colon and rectal cancers have stabilised or are decreasing throughout the EU, although there is a clear north-south divide. While northern and western Member States have the highest incidence and mortality rates, the south has the lowest. 42 Relative survival rates are defined comparing mortality of people who suffered cancer with mortality levels of the general population. 43 Source: Société Française de Santé Publique (2000): “Health and Human Nutrition: Element for European Action”. 42 The social dimension of health Section 2 Male incidence rates of cancer of the stomach are twice those of women. Here again there is a clear northsouth divide where rates in southern countries at least double those of northern ones44. butory factor to, amongst other things, suicides, homicides and accidents. Considering the recent trends in prevalence, paranoia, schizophrenia and manic-depressive illness seem to have stabilised, whereas dementia and disorders (such as depression, anxiety and alcohol or drug dependence) related to responses to social circumstances, appear to be increasing. Mental health is discussed in more detail in section 2.4. Cancer of the lip, oral cavity and pharynx is especially high for French men. Indeed, they have the second highest incidence level in the world, after India. Levels in men in the rest of EU Member States are growing. In comparison with male levels, those of women are considerably lower. Neurodegenerative diseases of old age. Parkinson’s disease, with a prevalence rate ranging from 6 per 1,000 at age 65 to 30 per 1,000 at age 85 and over, and dementia are the most common neurodegenerative diseases among older people. There are two main types of dementia: Alzheimer’s disease, when no cause of dementia can be identified, (70% of all dementia cases) and vascular dementia, caused by strokes in the brain. As in the case of Parkinson’s, dementia increases with age. However, Parkinson’s disease affects more men than women above the age of 75, while more women than men are affected by dementia (particularly Alzheimer's) after the age of 80. The geographical distribution of non-Hodgkin lymphoma is very uniform throughout the EU, with incidence levels increasing over the past 25 years. Viral infections can account for some cases and AIDS has also increased the risk. There is a large variation in the incidence and mortality levels of kidney cancer in the EU. The highest levels are found in the northern Member States, including Germany, and the lowest in Portugal. Smoking is a major factor in this type of cancer. Leukaemia is 60% higher in men than in women but shows no clear geographical distribution. Incidence rates have been mainly stable. Musculoskeletal diseases. Chronic rheumatic diseases are the cause of a large number of cases of disability, creating high costs in terms of health care and loss of productivity. However, comparable data only exist for osteoporosis, which shows an increasing incidence of hip fractures, particularly affecting women after menopause. As the population is ageing, it is likely that this trend will continue. Musculoskeletal diseases are a concern for work-related health problems, as discussed in more detail in section 2.2. Levels of cancer of the pancreas are high in the north and low in Greece, Portugal and Spain, with similar patterns for both sexes. Although its incidence is much lower than that of stomach, its fatality rate is higher. Melanomas are much more prevalent in the north than in the south. However, incidence has been growing sharply all over the EU. In comparison to its incidence, mortality rates are relatively low. Liver cancer is six times more common in men, and also five times greater among women, from southern Member States compared to those living in northern ones AIDS. In 1998, there were over 12,000 new cases of AIDS, making the EU cumulative total since 1983 over 200,000 cases. For the third consecutive year, there was a reduction in the number of new cases – a drop of 23% between 1997 and 1998. The groups with the largest reduction of new cases were injecting drug users (IDU) and homosexual and bisexual men. However, among men, IDUs still account for the highest number of new cases diagnosed. Women accounted for 21% of the adult/adolescent cases diagnosed in 1998, of which nearly half were heterosexually infected, often by an IDU partner. Nearly half of all new cases are within the 25 to 34 age group. Mental and behavioural disorders. The magnitude of the burden of mental disorders is generally underestimated. Although no comparable data on specific mental diseases is available and less serious disorders are frequently unregistered, estimations of the prevalence of mental illness vary between 9% (self-reported) and 17% (clinically diagnosed) of the total population. Neuro psychiatric disorders seem to be the second most important cause of disease burden in Europe – and the first if only disability, and not premature deaths, is considered - after cardiovascular disease, with an estimated 20% of all the DALYs lost in 200045. Mental problems are also an important indirect cause of death as a contri- All countries have experienced a decline in the incidence of new cases since the mid-1990s, with the exception of Portugal where there has been a slight increase. 44 As the socio-economic status has increased in southern Europe, the incidences of stomach cancer has reduced. 45 Source: WHO: “The European Health Report 2002”. 43 Section 2 The social dimension of health Graph 14 AIDS incidence rates per million population, with adjustments for reporting delays, - 2001 110 100 90 90 80 80 70 50 40 40 29,4 25,0 21,8 10,5 13,9 6,8 8,1 D EL 9,5 4,2 E 30 30 21,3 20 2,8 5,3 F IRL I L NL A FIN S 11,2 11,3 10,7 11 10 20 6,7 10,1 11,3 10,4 8,9 6,4 10 5,1 10 3,3 4,7 P 20 15 12,2 12,8 0 0 DK 40 30 11,3 0 EU 15 BE 40 60 50 20 50 45,2 70 58,0 60 10 50 110 105,8 100 30 Graph 15 Tuberculosis incidence rates per 100,000 people - 2000 0 EU 15 BE UK Source: Eurostat DK D EL E F IRL I L NL A P FIN S UK Source: Eurostat Congenital anomalies. The recent decline in the incidence of AIDS is thought to be due to the increasing use of highly active antiretroviral treatment since 1996 and the fact that HIV incidence peaked in the mid 1980s. However, the current decline in AIDS does not mean that HIV is declining; HIV reporting data suggests that its transmission level has remained stable in recent years. Around 2.4% of births were affected by a major congenital anomaly during the period 1980-94 in 15 European countries (12 Member States plus 3 non-Member States), with important geographical variations. Limb defects are the most frequent (25% of all cases), followed by congenital hearth diseases (almost 23%). The share of cases diagnosed as anencephaly or Down syndrome during pregnancy is increasing, although geographical differences still exist. Other sexually transmitted diseases. From this group of diseases, those with statutory notification (syphilis and gonorrhoea) have decreased over the last 20 years. The EU incidence rate of syphilis reduced from 5.6 (per 100,000) in 1985 to 1.5 in 1997, while gonorrhoea has decreased from 60.2 per 100,000 in 1986 to 7.6 in 1997. Recent data shows, however, a recent increase of gonorrhoea in France (1998) and England (1997). At present, genital warts, non-specific vaginitis, non-specific urethritis, genital herpes and chlamydia appear to be the most common sexually transmitted diseases. Other diseases. ● Malaria: the EU incidence has increased from 0.6 per 100,000 in 1974 to 2.9 in 1997, with data ranging from 0.1 in Greece to 9.2 in France. This is mainly due to people contracting malaria in endemic countries. ● Hepatitis C: its prevalence in the whole population varies among Member States: up to 1.5% in Greece compared with 0.9% in Belgium. But the prevalence levels are as high as 70% in specific subgroups, such as drug users. ● Hepatitis B: its incidence, influenced by the onset of the HIV epidemic among adults with co-infections of both diseases and by massive vaccination levels since 1994, is decreasing (EU average of 4.1 per 100,000 in 1997) but has not yet been eradicated. An increase in incidence was observed in Portugal between 1992 and 1995, after which the values decreased sharply. ● Influenza: this infectious viral disease still causes widespread sickness as well as excess mortality among older people. ● Diabetes mellitus: Incidence of this chronic disease, caused by inherited or acquired deficiency in the production of insulin by the pancreas, is increasing due to an ageing population, unhealthy diet, obesity and sedentary lifestyle. National prevalence rates range The specific issue of sexually transmitted diseases amongst young people is discussed in section 2.2. Tuberculosis. There was a decrease in tuberculosis in most Member States until 1975, when it levelled off before again increasing in some countries in the late 1980s and early 1990s. The recent epidemic was strongly influenced by the level of AIDS among young adults. Approximately 45,000 new cases were registered in 2000 for the whole EU, 61% of which were men. Furthermore, it is a major health problem in Portugal - 45.2 cases per 100,000 inhabitants in 2000 compared with an EU average of 12.2. Although there are some cases of tuberculosis in older people due to reactivation of former infections, the majority of the cases come from newly infected people. 44 The social dimension of health Section 2 from 2.1% in Ireland to 5% in Italy, with an EU average (without Greece) of 3.4% in 1994, but the number of cases could increase by almost 20% this decade, due to an increase in the prevalence of causal behaviour. ● Within every Applicant Country, women have longer life expectancy then men, but the size of the difference varies. In the Baltic States the difference between male and female life expectancy is as high as 11 years. These poor levels of health in the Baltic States therefore particularly affect men, which may indicate that they are associated with aspects of gender roles or gender related life-styles. Asthma and allergic diseases: These are the most common and rapidly increasing chronic diseases among young people, affecting more than one third of them at some time in their life. In the UK about one-third of children aged 13 to 14 suffer from recurrent symptoms of asthma, and almost 30% in Ireland. In contrast, prevalence rates are around 15% in Finland, Germany, Sweden, Belgium and Austria, and lower still (around 10%) in southern Europe. Greece has the lowest reported incidence rate, 3%. These variations may, in part, be explained by environmental factors, but – as they are based on self-reported incidences – may also be explained by levels of awareness46. 2.1.4 … with higher incidence of infectious disease… The incidence of infectious communicable diseases is high in central and eastern candidate countries and in some cases, for example tuberculosis, it has increased alarmingly since the start of the transition period. Similarly, sexually transmitted diseases, such as syphilis, show increases over the last decade in some candidate countries, in contrast to the continuously low incidence inside the EU. The situation of HIV infection shows more complex variation; Latvia has by far the highest levels of HIV infection (probably due to drug use). However, the remaining applicant countries have infection levels below or even substantially below that of the EU average, with the lowest levels found in the Czech Republic, Slovakia and Turkey. Mortality and morbidity in the applicant countries: an overview Changing demographic and health trends in the applicant countries... Due to past political regimes, central and eastern European countries experienced a paternalistic State healthcare system which created a passive attitude towards health on the part of patients. Preventative health care was largely not considered to be important and primary health care was often underdeveloped. Furthermore, spending on health was low as a percentage of GDP, in comparison to industrialised countries in western Europe. As a consequence, the rapid improvement in life expectancy in the post-war period, which was due to a reduction in infectious diseases (when central and eastern European countries and the former USSR had the same mortality rates as western Europe) was not seen after 1965, when life expectancy levels increasingly diverged between eastern and western Europe. … as well as non-infectious diseases, accidents and violent deaths… For non-communicable diseases, mortality from noninfectious diseases is far higher in candidate countries than in the EU generally, and almost all show significant mortality rates from chronic illness such as heart disease, diseases of the circulatory system and cancer. Only Malta has the same or better than EU average rates with respect to these diseases, followed by Slovenia. However, there is a different pattern for cardiovascular diseases and for cancers. Cardiovascular disease was especially high in Bulgaria, Latvia, Estonia, Romania and to a lesser, extent Hungary. Cancers were especially high in Hungary, Slovakia, Czech Republic, Poland and Romania. This might reflect different levels of environmental pollution or different kinds of lifestyle in these regions. The start of the political transition in the central and eastern candidate countries, which brought a downturn in the economy, had dramatic demographic consequences, with declining birth rates, rising mortality rates and decreased life expectancy. Finally, the economic recovery of the latter half of the 1990s has created a general decline in death rates and a general rise in life expectancy, while infant mortality has also been declining. However, the intensity and the timing of this recovery vary by country, with better mortality and morbidity figures in the central European candidate countries compared with the Baltic States or Romania and Bulgaria47. One lifestyle factor which plays a role in many causes of mortality is alcohol consumption. It is likely that alcohol is a more significant factor in higher rates of sudden cardiac death48 and cirrhosis in central and eastern European acceding States and candidate countries than in the EU. Mortality rates from injuries, especially road traffic accidents, drowning and fires, and from homicides and suicides, are also higher in these countries, which may in part be attributed to patterns of alcohol consumption. 46 Taken from European Commission Directorate-General for Health and Consumer Protection. (2000) “Report on the state of young people's health in the European Union”. Brussels: European Commission 47 By contrast, the situation is very different in Cyprus and Malta, where death rates are below the EU average (with female life expectancy being slightly below the EU average, and for men it is slightly above), while birth rates are higher but they have been declining steadily over the longer term. Finally, Turkey presents higher mortality and fertility rates compared with the EU average. 48 A. Britton, M. McKee (2000): “The relationship between alcohol and cardiovascular disease in Eastern Europe”. Journal of Epidemiological Community Health, (54) pages 328-332. 45 Section 2 The social dimension of health In conclusion, although health standards are currently improving in the candidate countries, they are generally lower than those existing in the EU Member States. At the same time, large differences among the applicant countries can be seen when health-related data are compared. In general, the standard of health and healthcare in Malta and Cyprus is most similar – and sometimes even better – than the EU. Within central and eastern European countries, the poorest health situation is found in the Baltic States, Romania and Bulgaria. Turkey has a lower level of development but has been catching up quickly, so that it is increasingly converging towards the average level of the other applicant countries. Furthermore, the contribution of scientific and technological changes to health care cost containment will also depend on the kind of diseases upon which efforts are concentrated. It should be noted that the two main causes of death are diseases of the circulatory system and cancer. Considering constant 1998 incidence rates by gender and 5-year age group, death caused by circulatory system diseases could increase by 23% over the next 25 years, while deaths from cancer would increase by only 8%. Therefore, technology changes to increase cost-efficiency in the care of circulatory diseases would contribute most to cost containment for an ageing population. However, present transformations in the age structure (ageing) as well as in the household structure of acceding States and candidate countries means that they will face similar demographic challenges with regard to health and health care in the current Member States. To understand how health care systems could potentially be affected by ageing, one methodology is to assume consistent behaviour for each age group cohort; that is, in future, people within a certain age cohort will make the same demands on the health care system as are currently made by people within that age group. It is important to note that this is only one of a wide range of possible future scenarios. Furthermore, it is difficult to know how close this scenario will be to the actual demand that will be placed on the health system over the next 25 years and, therefore, projections should be treated with caution. This notwithstanding, the scenario highlights, among other things, where (i.e. in which segment of the healthcare system and in which Member States) the demographic ageing shift is likely to place high pressure. This is outlined below. 2.1.5. Ageing and health cost The effect of demographic ageing on future health costs has become a focus for debate. The main drivers of future costs are related to the demand for, and supply of, health care. The resulting combination of these demand and supply forces are not yet known and projections based on these factors should be treated with caution. For example, a demand-side factor is the changing behaviour and lifestyle of the elderly; the generations born before World War II had significantly lower educational levels than the post-war baby-boom generation – a trend that has continued in subsequent generations. With better educational attainment, higher incomes and improved lifestyles, people may make fewer demands on health care services. In general, people who are better educated tend to make lower demands on the primary care system (consulting GPs), but higher demands on the secondary healthcare system (in-patient care). ● On the supply side there are also several factors of uncertainty. One of the major factors relates to technological change and the objective of finding new methods of diagnosis and less intrusive treatments. Some of these progressions may well reduce cost, for example new medication may be able to replace some types of in-patient care, or non-invasive surgery may shorten the length of stay for in-patients. However, this cost-saving effect is by no means certain; it is possible that new medication may have high financial costs, or that new treatments to prolong life may lead to longer periods of in-patient care. In other words, a hypothetical cancer vaccination may well drastically reduce financial costs, but more efficient chemotherapy would not necessarily do so. This makes it very difficult to predict the impact of scientific and technological changes on health sector costs. The graph below estimates that over the next 25 years the total numbers of GP consultations will increase by one sixth49. The increase will be over a fifth in Ireland, Greece, the Netherlands and Austria. Even if the number of GPs were to be stable, instead of declining as medical demography suggests, this increase in demand would greatly increase pressure on GPs. If there were a reduction in demand due to better educated generations, it may not offset this demographically driven increase in pressure. Moreover, it can be assumed that scientific and technological changes will Graph 16 Effects of demographic ageing on the primary care system Increase (%) in the number of consultations of general practitioners between 2000 and 2025. Hypothesis of constant behaviour per age group* 40 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 0 0 B DK EL E IRL I NL A P UK Aver. Note: *Constant number of nights in hospital (1998) for the following age groups: 15-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75-84, 85+; 1998 data as from ECHP - UDB, 12/2001 Source: Demographic projections as from Eurostat 2000 (Baseline scenario) 49 Data is currently only available for 10 of the 15 Member States. 46 The social dimension of health Section 2 not concentrate their productivity effect on the primary care system. ● Along with the volume of people involved, the trend towards increased life expectancy could imply that the elderly will place more demands on the health system over an increasing period. Therefore, the age pattern of specific disability risks is a particularly pertinent issue here, as discussed in the following box. For the secondary sector, pressure from the demographic process of ageing seems likely to be higher. The graph below shows an estimated increase of 23% over the next quarter century, with higher increases in the same four Member States cited above. However, the secondary sector might well be where new technologies have the greatest impact on cost-efficiency. As a general conclusion, it is clear that the impact of ageing on healthcare costs is a subject that needs more research. Graph 17 Effects of demographic ageing on the secondary care system Graph 18 Number of deaths in EU-15, 2000-2050 Increase (%) in the number of consultations of general practitioners between 2000 and 2025. Hypothesis of constant behaviour per age group* 50 50 45 45 40 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 0 6 000 000 5 000 000 5 000 000 4 000 000 4 000 000 0 B DK D EL E IRL I NL A P UK 3 000 000 Aver. 3 000 000 2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 Note: *Constant number of nights in hospital (1998) for the following age groups: 15-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75-84, 85+; 1998 data as from ECHP - UDB, 12/2001 Source: Eurostat 2000. Demographic projections (Baseline scenario) Source: Demographic projections as from Eurostat 2000 (Baseline scenario) ● 6 000 000 Given the ageing population and the different health cost per age, this demographic projection suggests that, on average within the EU, the volume of total health expenditure may increase by almost 0.6% per year over the next quarter century, in real terms. Some researchers argue that rising expenditure should be related to the proximity of death, rather than to the age shift, as most expenditure on health care takes place in the last years of life50. The baseline scenario for the number of deaths in the EU (as illustrated in the graph below) suggests a similar trend to total health expenditure, 0.6% a year on average by 2025. The chart shows little movement before 2010, and a steady increase at 0.9% per year afterwards – when mortality is likely to be at the highest for the post-1945 baby-boom generation. Furthermore, examining the different indicators related to age-specific behaviours and to demographic ageing (evolution in age distribution and the number of deaths), the overall conclusion is that over the next 25 years pressure derived from ageing will be highest in Luxembourg, the Netherlands and Ireland. All other Member States will experience similar levels of pressure, with the exception of the UK and Sweden, where the pressure is likely to be more moderate. 50 Lubitz and Riley (1993) "Trends in Medicare payments in the last years of life" New England Journal of Medicine 328: 1092-6; Zwzeifel, Felder et al. (1999) "Ageing of Population and Health Care Expenditure: A red herring?" Health Economics vol 8: 485-96. 47 Section 2 The social dimension of health Scenarios for the future: using a demographic approach* Europeans live longer, but do the years added to life imply more disability? With increasing life expectancy, is there a shift in disability prevalence to a higher age? One would expect that the number of disabled and incapacitated people in Europe will increase rapidly over the coming decades as an increasing number of people enter the ages of high disability rates. However, this will not necessarily be the case if the age pattern of specific risks of disability continues to shift to higher ages, i.e. if, at any given age, the risk of impairment declines. The first of the three graphs over the page shows the population of the EU-15 in 2000 by age, sex and disability status as measured by the most recent health surveys. Here the darker area includes both the severely and moderately incapacitated. The age pyramid shows that at present there is a larger number of incapacitated women aged 55 to 80 in comparison to men. The second and third graphs on the following page present two alternative scenarios for the year 2030. Both are based on an identical projection of the total population of the EU-15, which includes the assumption of two years gain in total life expectancy per decade. ● The second graph [Graph 20] presents the projected age pyramid under the assumption that currently observed age-specific proportions of incapacitated people do not change over time. This implies no change in the probability of becoming incapacitated, leading to an increase in the number of incapacitated people, from the current figure of around 60 million to around 75 million in 2030. ● The third graph [Graph 21] assumes that while life expectancy increases by two years per decade, the schedule of age-specific proportion of people who are incapacitated also shifts to higher ages by two years per decade. For example, this means that by the year 2030 the risk of being suffering some incapacity at age 70 is equal to that at age 64 in 2000. For this scenario, the results show almost no increase in the number of incapacitated people in Europe with the total number only increasing from 60 to 62 million by 2030. Extended to 2050, this scenario will even result in slight declines in the population suffering some incapacity. In conclusion, the number of elderly people that will be in need of assistance and care will not necessarily increase as a consequence of population ageing. The key factor lies with the future trend in age-specific risks of becoming incapacitated. This seems to be an area where preventive medicine and public health measures can make a big difference. This reference is taken from work produced by the European Observatory on the Social Situation, Demography and Family. 48 The social dimension of health Section 2 Graph 19 Profile of EU total population, showing proportion that are incapacitated European Union, 2000, Total and Hampered Population Year of birth Age 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 4,0 3,5 3,0 2,5 2,0 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Females Males 1,5 1,0 0,5 0,0 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 Population (millions) Source: Eurostat Graph 20 Projection of incapacited population to 2030, no change in incidence of disability assumption European Union, 2030, Total and Hampered Population Scenario constant proportion hampered Age Year of birth 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 Females Males 4,0 3,5 3,0 2,5 2,0 1,5 1,0 0,5 0,0 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 4,0 Population (millions) Source: Eurostat Graph 21 Projection of incapacited population to 2030, change in age of incidence of disability assumption European Union, 2030, Total and Hampered Population Scenario shifted proportion hampered Year of birth Age 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 4,0 3,5 3,0 2,5 2,0 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Females Males 1,5 1,0 0,5 0,0 0,0 0,5 Population (millions) Source: Eurostat 49 1,0 1,5 2,0 2,5 3,0 3,5 4,0 The social dimension of health Section 2 2.2. Socio-economic determinants of health. ● Factors related to the physical and social environments have an important impact on health status. In this context health status is not only influenced by the financial resources available for healthcare, but also to the whole range of socio-economic and environmental determinants of exposure to specific health risks. A number of inter-related factors have to be considered when defining a person's socioeconomic status including educational levels, occupational skills, employment status, influence within the work place, life-style considerations and the extent of an individual's inclusion in social networks. All these factors interact in a complex manner, determining the level of exposure to specific health risks. As this exposure is unequally distributed across society, it can, to some extent, explain the existence of health inequalities. ● Human health depends on the availability and quality of food, water, air and shelter. These environmental conditions are, however, dependent on the way in which we manage our resources. Thus, rapid urbanisation has created particular problems in many cities, resulting in air pollution, unacceptable noise, traffic congestion and accidents, insufficient sewage systems and, in some districts, poor housing conditions. Other health problems relate to contamination of water and food as a cause of many communicable diseases. However, these adverse effects are partially addressed through urban renewal, improved infrastructure, monitoring of pollutants and reinforced nutritional safety measures, which have reduced their prevalence. ● One of the key factors mentioned above is employment status, which is crucial to health status. High employment rates and low unemployment significantly reduce mortality, particularly as a result of reduced cardiovascular illnesses. The mortality risk for people out of employment appears to be five times that of those in steady employment. Moreover, perceived bad health and consultation of physicians is more common among the unemployed. Stress factors, linked to the threat of losing social status (social exclusion), may be part of the explanation for this trend. Even though social support and networks or 'informal jobs' may, to some extent, alleviate the negative impact of job-losses, a successful employment strategy could still contribute to achieving better health outcomes. ● Although employment has an overall positive impact on longevity and health, there are specific risk factors related to certain occupational sectors and job types - which are also linked to educational attainment and gender – that create certain work-related health problems, such as a relatively high frequency of accidents and work-related diseases. The majority of work-related health problems are musculoskeletal, followed by stress, then pulmonary and cardiovascular disorders. Along with the type of industry and occupation, which determine the nature of work-related health problems, the type of work contract (temporary) or work patterns (shift work) are also important. ● The costs related to preventive or curative healthcare should be considered in relation to the number of workdays lost, and the consequent loss of production and income, due to work related accidents and bad health. In total, accidents and health problems at work caused 500 million lost workdays in the EU in 1998/99. The total cost of work-related sickness is far reaching and includes issues such as employment of temporary staff, recruiting and training new staff and workers' sickness benefits. ● Income and income inequality, particularly when poverty is also present, are strongly associated with health status. Access to preventive and curative healthcare (related to insurance and high income) is important for health, not only regarding access to care (e.g. hospitalisation, consultations), but also quality of care (e.g. treatment, communication and follow-up). It should be noted that the incremental health benefits resulting from reduced income inequality are particularly important when poverty is also present within society, especially in view of the fact that incremental health benefits diminish with higher income. ● Finally, the relationship between socio-economic factors and health status are not easily discernible. The mechanisms that trigger a connection do not only depend on aggregates, such as income and employment, but also upon individual experiences and social context throughout life, along with other factors, such as rank and trust, which again are related to the hierarchical or egalitarian structure of our societies. 51 Section 2 The social dimension of health Introduction Graph 22 Mortality (AMI), males and unemployment, 1995 The overall health status of the European population is a product of several determinants, among which environmental and socio-economic factors are of particular importance, while healthcare systems plays a more limited role. IRL Mortality (AMI) males /100 000 As health is related to general living and working conditions, policies from different domains, such as employment, education, social protection and housing, can make major contributions to the achievement of health policy objectives. The links between health status and the overall context of human life make it important to pay due attention to these factors and to further develop synergies between the relevant social policy areas and healthcare systems. 2.2.1. Impact of unemployment on AMI without protective effect of mediterranean diet and other aspects of lifestyle 200 FI UK 150 S AT NL DE DK 100 Impact of unemployment on AMI with protective effect of mediterranean diet and other aspects of lifestyle 5 P ES IT LUX FR 50 5 10 15 Unemployment rate % 20 Source: Prof. H. Brenner: "Unemployment and public health" employment status on the one hand and mortality on the other can be explained in terms of status and lifestyle in the broadest sense of the terms. The role of employment and unemployment The importance of socio-economic status for health and mortality (disregarding other characteristics such as gender and age) has been highlighted in a number of epidemiological studies. The various dimensions that characterise social status lead to different exposures to health risks53. Furthermore, it has been shown that lower socio-economic status is related to higher mortality54, and that healthcare systems tend to offer less appropriate treatment to lower status categories. In this context it is important, again, to note the cumulative positive or negative impact on health of any changes in socio-economic dimensions during the life course. Employment status has an impact on health status. High employment rates, or low unemployment, together with high average national wealth, have been shown to reduce mortality rates significantly, within a time lag, particularly as a result of reduced cardiovascular illnesses51. These parameters are shown to have a clear impact upon mortality, controlling for other factors. In fact, to a large extent changes in the employment rate explain the changes in the mortality rate. These findings are also confirmed when comparing not only annual levels within each of the 15 Member States, but also annual changes to those levels. Similarly, annual, country-specific unemployment rates across the EU partially account for differences in heart disease mortality. In general, perceived bad health is more common amongst the unemployed, homebound or retired than it is for people active in the labour market55. For example, Graph 2252 shows that unemployment has an adverse impact upon life expectancy but the impact of high rates of unemployment is different in the Mediterranean countries than in other EU-countries. However, it is worth noting that where the informal economy, or similar social settings, offer opportunities to include people who are normally not active in the labour-market the negative health effects may be attenuated. In this case, the social network becomes a 'buffer' against negative economic changes (see section on income and poverty below). Graph 23 General Practitioner consultations in the last 12 months 8 8 Active Furthermore, many studies at the individual level point to a positive relationship between unemployment and illness or disability, both in physical and mental terms for example, the relatively high suicide rates among young unemployed people. The relationship between Inactive 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 Total 15_24 25_34 35_44 45_54 55_64 65+ Note: Average number Consultations of general practitioners over the past 12 months (Source: ECHP - UDB, 12/2001). Average B, DK, EL, E, IRL, I, NL, A, P, UK. Source: ECHP 12/2001 51 Prof. H. Brenner: "Unemployment and public health", European Commission, Directorate General for Employment and Social Affairs. Presented at a seminar in Brussels (May 2002) with contributions from Professor Perucci and Professor Siegrist. 52 Contribution from Prof. H. Brenner: The graph shows the statistically significant relationship between the rate of unemployment within and outside the Mediterranean countries and male acute myocardial infarction (AMI). The combined impact of unemployment rates and the protective Mediterranean lifestyle factors explains 81% of the variation among EU-countries of male AMI mortality rates. 53 These dimensions are generally the result of macroeconomic and social policies. 54 During the 1980s life expectancy, at the age of 60, was another 22 years for engineers, against 17 years for manual workers. (see Annette Leclerc et al: Les inégalités sociales de santé, Editions La Découverte, Paris 2000). 52 The social dimension of health Section 2 The EU strategy on health and safety at work 'inactive' people consult General Practitioners (GPs) more often56 (5.1 per year) than active people (2.4 per year). Health and Safety at work is one of the European Union's most important social policy sectors. Health at work is not only the absence of accidents or occupational illnesses, but involves physical, moral and social wellbeing which are important for the quality of work and the productivity of the workforce. On the other hand, becoming active again or reemployment does not necessarily reduce health risks. The new jobs may be precarious, temporary, uncomfortable or stressful, which all result in additional occupational health risks. A new Community strategy on health and safety at work for the period 2002-2006 has been developed, taking into account changes in society and the world of work*. The strategy adopts a global approach to wellbeing at work, based on preventative measures and building partnerships between all players in the areas of employment, health and safety. As well as aiming to create a genuine culture of risk prevention through better application of existing law and improving people's knowledge of occupational risks, Member States will also be called upon to adopt national objectives for reducing occupational accidents and illnesses. It has been shown57 that the mortality risk for people out of employment is almost five times that of people in steady employment. Furthermore, for people returning to the labour market the mortality rate is almost 1.5 times higher than that of the steadily employed. Although the results compare well with other studies58, the figures may, of course, hide other underlying factors, such as existing health problems; i.e. people with such problems may be more likely to lose their job. Table 1 Occupational Lifecourses and Mortality Torino 1991-96 (Occupation 1976, 81, 86, 91) * COM(2002)118 - Adapting to change in work and society: a new Community strategy on health and safety at work (2002-2006) Cardano et all, 1999 Occupational Lifecourse Steady employment Unemployment followed by employment Intermittent employment Employment followed by retirement (white collars) Employment followed by retirement (blue collars) Employment followed by unemployment Steady unemployment Unemployment followed by out of labour force Steadily out of labour force % Relative risk 73.8 2.5 6.6 6.3 6.0 3.3 0.4 0.4 0.8 1.00 1.43 1.52 1.61 2.22 2.29 2.61 3.85 4.81 sense of control' to be crucial predictors for health and mortality. Such imbalance between workload and perceived control may result in temporary absenteeism and subsequent return to work. This whole process is influenced by individual factors (biological and psychological), employment factors (work organisation, stress and accidents) and societal factors (environment)60. Although this may appear obvious, it is important to underline that absenteeism is in part a reflection of the interplay of various workplace factors, which could be appropriately adapted. It has been shown61 that the quality of work – the creation of "better jobs" – has a positive impact upon labour market participation, particularly among women and older people, and appears to underpin labour productivity. The relationship between quality in work and work-related health problems is analysed in more detail below. Source: Cardano et al. The impact of health status on employment status. In fact, while employment status affects health, empirical research also shows that the inverse relationship holds true: bad health, whether work related or not, causes absenteeism for people in the workforce. Or put another way: a job is good for your health, but a good job is better. Stress-related health problems may arise from an imbalance between workload demands and a worker’s capacity to deal with those demands (see also the "demandcontrol-support model" discussed later in this section). In fact, some studies59 have shown 'rank' and 'having a Absenteeism represents a cost to society and continues to grow. Within this context it is worth noting that work related accidents and health problems caused an annual loss of 500 million working days in 1998/9962. 55 Eurobarometer 57.2 spring 2002, p73 56 Of course, they may have become inactive due to bad health rather than the other way round. 57 From a presentation by Professor C. Perucci at DG Employment and Social Affairs, Brussels, May 2002. The figures are based upon the Turin longitudinal census mortality study (1976, 81, 86, 91) – Cardano et al, 1999. 58 Annie Mesrine: La surmortalité des chômeurs-un effet catalysateur du chômage?; INSEE, Economie et statistique no 334, 2000. See also: L.Berkman &I.Kawachi (ed): Social Epidemiology, Oxford University Press, 2000. (chap 6). 59 M. Marmot: The influence of Income on Health. Health Affairs (2002). 60 European Foundation for the Improvement of Living and Working Conditions: Preventing Absenteeism at the Workplace, Dublin, 1997. www.eurofound.ie. 61 Employment in Europe 2002: Synergies between quality and quantity in European labour markets. (ch 3). European Commission Directorate-General for Employment and Social Affairs. 62 European Foundation for the improvement of living and working conditions: Third European survey on working conditions 2000. www.eurofound.ie. On average 1.26 days per employee were lost due to occupational accidents in 2000 and 1.80 days due to work-related health problems. Total employment in 2000 was 164,702,000 people. 53 Section 2 The social dimension of health Table 2 Graph 24 Standardised prevalence rate of work-related health problems by diagnosis group and age, EU-15, 1999 The process of becoming ill, being absent, recovering and resuming work 8000 8000 Pulm 7000 M_S 7000 6000 Stress 6000 Workload 5000 Other 5000 Total Balance Capacity Health problems Absence from work Threshold of absenteeism Threshold of reintegration Workplace factors Societal factors Return to work 4000 4000 3000 3000 2000 2000 1000 1000 0 0 15_24 25_34 35_44 45_54 55_64 65+ Total Note: Pulm=Pulmonary disorders; M_S=Musculo-skeletal disorders; Stress=Stress, depression, anxiety; Other=other not elsewhere mentioned. Source: Eurostat Individual factors culoskeletal disorders, 14% as “stress, depression and anxiety” and 6% as pulmonary disorders. Schematic framework from: “Preventing Absenteeism at the Workplace (Dublin Foundation for the Improvement of Living and Working Conditions) According to the third European survey on working conditions (2000), 27% of all workers in EU-15, against 40% in the acceding States and candidate countries, think that their health or safety is at risk because of their work, particularly in the construction, agriculture, fishing, transport, manufacturing and mining sectors. Craft workers, machine operators and agricultural workers were more exposed to noise, vibrations, fumes and dust, tiring work positions or heavy loads than other occupational categories in general, and this trend has been increasing over the past decade. At the same time, the pace of work appears to have become more acute for an increasing number of respondents, particularly machine operators and craft workers. Work-related health questions can be examined using a variety of indicators, ranging from work-related health problems in general, to more specific areas, such as occupational diseases, accidents at work and accidental injuries. Each of these areas will be addressed below. Age is shown to be a strong determinant: the overall standardised prevalence rate is lowest in the 15-24 age group and then rises steadily to a maximum in the 55-64 age group. ● Different types of industry are associated with different types and likelihood of work-related health problems. The health, social work and education sectors have the highest incidences, particularly (twice the overall average) for stress, depression and anxiety. ● A person's occupation is also a factor in determining the likelihood and type of work-related health problems. Stress is six times more likely for those in the highest functional position64 (senior officials and managers) than those in the lowest. Conversely, the incidence of musculoskeletal disorders is halved in the lowest positions compared to the highest, with severity also declining significantly. Within the context of work-related health problems it has also been shown65 that there is a quantified relationship between the risk of heart disease and a stressful work situation66, where there are high demands, little control and also little social support. It is worrying, therefore, that 33% of all employees report67 that they do not control the pace of their work, and 24% are continuously working at high speed. Similar figures are reported in the acceding States. This is particularly true in precarious jobs and among those with low socio-economic status68. A continuous high pace of work gives rise to accumulated health risks related to stress, and generates muscular pain, backache, headache, and overall fatigue, which may trigger negative health outcomes and absenteeism. The prevalence of work-related health problems depends on a number of factors. Below are some of the main conclusions on work-related health problems, using the standardised prevalence rate (SPR)63: ● ● The standardised prevalence rate varies significantly between Member States, with Spain and Portugal below half the EU average, and the three Nordic Member States well above the average. Over 40% of work-related health problems are registered as mus- 63 From Eurostat data, using overall standardised prevalence rates (i.e. the proportion of the population, standardised for comparative reasons according to age and gender, with a disease or disorder at any time of the year). 64 ISCO (i.e. International Standard Classification of Occupations). See also Eurobarometer 56.1 (www.europa.eu.int October 2002). 65 Prof J.Siegrist in his submission to the Brussels seminar 21.05.2002 on "Unemployment and public health". 66 See also European Agency for Safety and Health at Work, Bilbao, http://europe.osha.eu.int 67 Third European survey on working conditions 2000 (see above) 68 Disregarding the social determinants of public health it should not be forgotten that an ageing workforce (demographic determinant) will become more exposed to work-related health problems. See also Eurobarometer 56.1. 1 (www.europa.eu.int October 2002) 54 The social dimension of health Section 2 ciencies. Increased participation in work organisation, including training and lifelong learning activities, generates new behavioural attitudes which motivate employees and reduce stress-related illnesses. Adding a third dimension, related to social support in the work place, underlines the importance of social networks as a 'buffer' against ill health. Graph 25 Percent of employees having no influence over their pace of work, by contract type 60 60 51 50 50 42 40 40 35 33 32 30 30 20 20 10 10 The prevalence of occupational diseases. 0 Apprenticeship Indefinite contract Fixed-term contract Temporary agent contract All employees Occupational diseases mainly affect older workers those aged 56 and over represent 43% of cases but only 10% of the workforce. Workers below the age of 36 constitute only one sixth of cases, while they represent close to half the workforce. The following bullet points are the main facts concerning occupational diseases: 0 Source: The European Foundation for the improvement of living and working conditions - 3rd survey on living and working conditions, Dublin 2000 Stressful situations are often related to changing work situations and job insecurity, which are more prevalent among employees on temporary contracts. In 2000 some 28% of men and 29% of women perceived their jobs as being stressful, mostly among professionals, technicians and managers. Graph 26 Occupational diseases, EU-15. 1995 Number of cases per age group The relationships between stress and health are partly direct and partly indirect, with the former influencing the neuro-endocrine system and the latter resulting in unhealthy behaviour related to smoking and drinking. These relationships are illustrated by the diagram below, which summarises research into work organisation and its impact upon health69. Workers with little or no control of their tasks and work situation who are expected to provide high performance levels are exposed to psychological strain and are prone to health defi- Table 3 30000 30000 25000 25000 20000 20000 15000 15000 10000 10000 5000 5000 0 0 <36 36-55 Source: Eurostat Graph 27 Occupational diseases, EU-15. 1995 Main cases per age group (percentage in each age group) The demand-control-support model (Karasek and Theorell, 1990; Johnson and Hall, 1998) 40 low 40 <36 36-55 56+ 30 30 20 20 10 10 DEM AND Relaxed high h hig High Strain L RO NT CO SUPPORT Passive high Active 0 Allergic effects Cancer Hearing disorders Irritant effects Pulmonary disorders Infectious diseases 0 Note: Irritant effects=irritant effects of the skin or mucous membranes low low 56+ Source: Eurostat - Quarterly Labour Force Data (QLFD). ● If work related demands are incontrollable and exceed the capacity of the worker the situation becomes stressful (“high strain” quadrant) and increases the risk of getting ill. If work demands are high but the worker exercise some control the situation becomes a challenge (“active” quadrant). The amount of social support for management and co-workers may act as a “buffer” on stressful situations. From: Guidance on work related stress, DG Employment, 1999. A small number of causes are responsible for a large share of occupational diseases. External causes account for over half of the total number of occupational diseases and, of these, noise accounts for over 60%. Respiratory diseases account for 17% of all the occupational diseases, and among these, close to one third are due to asbestos and one quarter to silicosis. 69 For a more extensive debate see: L.Berkman & I.Kawachi (eds): Social Epidemiology, Oxford University Press, 2000: chapter 5. 55 Section 2 The social dimension of health Occupational allergies represent close to 10% followed by musculoskeletal disorders (7%). The prevalence of these diseases varies with age. For example, allergic diseases, diseases with irritant effects on the skin or mucous membranes, and infectious diseases decline strongly with age and conversely cancer, hearing disorders and pulmonary disorders are positively correlated with age. ● ● States in 1998, but it was below half this average in Ireland, Sweden, Greece and the United Kingdom and over 40 in Germany, Spain and Luxembourg. 80% of work accidents involved men. Occupational diseases are mainly concentrated within the non-service sectors: 43% of all diseases are within the manufacturing sector, of which over 40% are due to noise. A further 12% occur in the mining industry, where silicosis accounts for 40%. Finally, 13% of all cases occur in construction. Although women represent 46% of the workforce, the female share in occupational diseases is much lower: only 18% on average70. This share is even lower for the reported occupational diseases of cancer (4%), hearing disorders (3%) and pulmonary disorders (4%). However women are over-represented in neurological disorders (55%) and, especially, infectious diseases (60%). ● Accidents can affect different areas of the body: The upper extremities of the body are affected in 41% of cases, lower extremities in 26% and the head in 9%. It is also worth noting that accidents affecting the head are responsible for 28% of fatal accidents. ● In 1998, the EU average number of fatal accidents at work (excluding transport accidents in the course of work) was 1.9 per 100,000 employed people72. There is variation across the EU, with rates below one in Sweden and the UK, while Luxembourg, Austria and Portugal displayed rates over 3.5. By age, the highest fatal accident rates are found within workers aged 45-54 years old (2.2) and especially in the age group 55-64 (3). ● Finally, commuting accidents resulting in four or more days absence totalled 420,000 in 1998, or 2.8 per 1,000 employed persons. Young workers (below the age of 25) were particularly over-represented; they represent 11% of the workforce, but 22% of commuting accidents, and their share is similar in the 2,067 fatal commuting accidents. Accidents at work result in a large amount of lost working days… Within the EU in 1998 there were almost 4.7 million accidents at work that resulted in four or more days of absence, which translates to 70 million lost working days. Above half (53%) of all work accidents71 result in over 30 days’ absence. More details on accidents at work are given below. …whilst the incidence of accidental injuries is affected by a number of factors. ● Graph 28 Accidents at work* per 1000 employed persons - 1998 60 60 50 50 40 40 30 30 20 20 Male workers are involved in more accidental injuries than female workers. If the overall average in the EU is indexed at 100, the respective incidence rates for men and women lie at 115 and 74. This male prevalence owes much to the gender distribution by sector and occupation. For example, in manufacturing, men and women show respective rates of 137 and 65. Graph 29 Relative standardised incidence rate of accidental injuries at work, by education attainment level and sex (mean rate for EU-15=100), 1999 200 200 Low 180 180 Medium 160 160 High 10 10 0 0 EU B DK D EL E F IRL I L NL A P FIN S UK** Note: *Accidents at work motivating 4 days of absence or more; ** Northern Ireland excl. Source: Eurostat 140 140 120 120 100 100 80 80 60 60 40 40 20 20 0 0 Total ● There are significant differences between Member States. The number of accidents at work per 1,000 employed people averaged 30 across all Member Men Women Note: Low=Pre-primary, primary and lower secondary education - ISCED 0-2 (1976); Medium=Upper secondary - ISCED 3 (1976); High=Total tertiary education - ISCED 5-7 (1976) Source: Eurostat 70 Please note that these statistics are not adjusted for hours worked or occupational sector. 71 When the period of absence is reported 72 This equates to almost 3,000 fatal accidents. This figure increases to 5,400 if road traffic accidents and accidents whilst using transport in the course of work are included. Male workers were involved in 94% of these accidents. 56 The social dimension of health Section 2 ● The level of educational attainment appears to be one of the main determinants, but only for male workers. For male workers with low, medium and high educational attainments, the incidence rates lie respectively at 179, 113 and 53. For women, the incidence rate remains within the much smaller range of 70 to 85. ● The age dimension is another strong determinant: The incidence rate decreases from the age group 1524 to the age group 45-54, although it increases again in the age group 55-64. Once an accidental injury has occurred, workers in the older age groups have significantly longer recovery periods, and also higher shares of permanent incapacity. Younger workers tend to have more cuts and burns while older workers are more exposed to fractures. ● Workers with a shorter working week have higher accidental injury incidence rates. The incidence rate for men working less than ten hours per week is five times higher than the overall male average. The corresponding figure for women working less than ten hours a week is almost twice the female average. The same can be said of workers on temporary contracts temporary workers show higher incidence rates and higher severity compared to permanent jobholders or trainees. work is higher, especially for younger workers and workers aged 55 and over. Night work also significantly increases the risk of more severe injuries for those over 55. Efforts to improve job quality and the employability of the working age population, through training or appropriate work organisation, in accordance with the Lisbon targets may have positive side effects on public health. Lower absenteeism due to work-related health problems would enhance labour productivity and output as well as alleviate spending on health care in the shortterm ('preventive approach'). In addition, as health care has a positive impact upon the ability of the unemployed or inactive population to work ('curative approach'), the accessibility and efficiency of health care systems become part of the inclusive, employment enhancing strategy pursued by Member States. The direct costs related to preventive or curative measures should be considered against the reduced socioeconomic costs and the marginal increases in output and income. European evidence from the early 1990s shows that the socio-economic costs (loss of output and property damage, costs of medical treatment and administration) due to work related accidents and diseases account for approximately 2% to 3% of GDP73. Evidence74 from the USA shows that the annual earnings of full-time working men in good health were 10% higher than those who were less healthy. Graph 30 Relative incidence rate of accidental injuries at work by frequency of shift work and age (EU mean rate = 100), 1999 200 2.2.2 200 180 180 Usually Sometimes Never 160 160 140 140 120 120 100 100 80 80 60 Education is important to health at the macro and individual level Educational attainment is an important dimension of socio-economic status and is related to the concept of human capital. At macroeconomic level a more educated labour force generates externalities that feed into employment, technological innovation and productivity. At individual level education also appears to enhance social capacities, expand individual opportunities, build self-confidence, increase skills and capabilities and promote a healthier lifestyle, by increasing the awareness of risks. According to a Eurobarometer survey only 50% of people with less than upper secondary education, against almost 75% of people with tertiary education, perceive their health to be "good" or "very good". This is an outcome that is reflected in the weighted index of self-perceived health and feeds into the perceived quality of life and life expectancy. 60 15_24 25_34 35_44 45_54 55_64 Source: Eurostat ● The impact of education and lifelong learning Accidental injuries have a high incidence rate in shift work: those who declare that they “usually” do shift work show higher incidence rates compared to those who do it “sometimes”. Workers who “never” do shift work have the lowest rates and their incidence declines with age. Similarly, where night work is more frequent, the incidence rate of accidental injuries at 73 European Foundation for the Improvement of Living and Working Conditions: Preventing Absenteeism at the Workplace. Dublin 1997. Also, see similar figures in WHO European Health Report 2002. 74 The Kaiser Commission on Medic aid and the Uninsured: "Sicker and Poorer-The Consequences of being Uninsured, May 2002. 57 Section 2 The social dimension of health Another indicator for health is the number of consultations of general practitioners over the past 12 months. The graph below clearly shows a relationship between educational attainment and the number of consultations within each age group over 24 years. On average, highly educated people tend to consult general practitioners 2.3 times per year against 4.6 consultations per year amongst those with low educational levels. These differences increase with age. Graph 31 Education and perceived health and life quality Quality spore (very good and good) 100 100 Quality of life Quality of health 80 80 60 60 40 40 20 20 Graph 34 Nights spent in hospital over the past 12 months per age, according to educational level (EU-15) 0 0 Educational level 1 2 3 4 8 Note: Educational levels: 1 (15); 2 (16 to 19); 3 (>20); 4 (Still students). 8 Total Low Med. High 7 Source: Eurobarometer 2002. 6 Graph 32 Self-perceived health (1998) 60 60 53 Low Med. High Total 50 46 43 40 27 Very good 2 1 1 0 25_34 35_44 45_54 55_64 65_74 75_84 85+ Source: Eurostat, ECHP - UDB 12/2001 Good Fair 8 5 Bad 4 2 2 A similar picture emerges if the number of nights spent in a hospital during the last twelve months is examined. People with a higher level of education tend to spend fewer nights in hospital during their working age, but the number of nights spent increases rapidly once retirement age is attained and exceeds that of other educational groups75. 3 0 Very bad Note: Low to High educational attainments compared to “very good” to “very bad” health perception. Source: Eurostat - ECHP - UDB 12/2001 Occupational function is often related to educational attainment and, therefore, reaffirms the expected outcome that managers and white-collar workers, typically with higher education, perceive their health in a more positive light than manual workers. Lifelong Learning An additional aspect of education is life long learning. More than 8% of the workforce participated in training activities in 200176. Such training reflects a commitment on behalf of employers and employees and the outcome could be expected to have a positive impact on work organisation and productivity at the enterprise level. If successful there is a multi-dimensional link to better health perception for the people involved, although other factors related to workplace stress and the pace of work may attenuate the immediate impact. Graph 33 Average number of Consultations of general practitioners over the past 12 months by educational level and age group, 1998 8 Low Med. High Total 6 4 4 2 2 0 0 2.2.3. Total 3 2 20 7 6 4 3 15_24 26 17 8 4 20 21 18 10 0 5 Note: Low=Pre-primary, primary and lower secondary education - ISCED 0-2 (1976); Medium=Upper secondary - ISCED 3 (1976); High=Total tertiary education - ISCED 5-7 (1976) 23 20 6 5 0 40 20 7 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 65+ The role of environmental conditions Sustainable development is a fundamental objective of the European Union. Note: Low=Pre-primary, primary and lower secondary education - ISCED 0-2 (1976); Medium=Upper secondary - ISCED 3 (1976); High=Total tertiary education - ISCED 5-7 (1976); Average B, DK, EL, E, IRL, I, NL, A, P, UK Health concerns constitute one of the core domains singled out by the European Council in Gothenburg in June 2001, when launching the European Strategy for Source: Eurostat, ECHP - UDB 12/2001 75 However, as already mentioned, other dimensions related to educational attainment like the work environment or social relations also interfere with the perception of good or bad health. 76 Source: Eurostat (statistics on participation in training for those aged between 25 and 64). 58 The social dimension of health Section 2 Sustainable Development. It highlighted the need to respond to citizens' concerns about the safety and quality of food, use of chemicals and issues related to outbreaks of infectious diseases and resistance to antibiotics. Lead-in-air concentrations also fell considerably during the second half of the 1980s as a result of the phasing-out of permissible lead levels in petrol. In the urban areas of central and eastern Europe sulphur dioxide concentrations were reduced during the last decade as a result of technical advancements and lower economic activity. The environment impacts on human health. Human health depends on the availability of quality food, water, air and shelter. The positive changes since World War II in basic health indicators, such as life expectancy and mortality, are due largely to alterations in lifestyle and improvements in medical care, but they also result, in part, from improvements in living and environmental conditions. A further source of pollution is "black smoke" – or particulate concentrations – which has been increasing in several cities, especially in central and eastern Europe, and also in southern Europe. Concentrations of nitrogen oxides and carbon monoxides are increasing in all European cities, mainly due to growing urban traffic. In western European cities, road traffic is a significant contributor to emissions, ranging from 30% to 50% of total nitrogen oxides and 90% of carbon monoxide emissions. It is also important to note that many environmental factors – such as air pollution, water pollution, food contamination, high noise levels or traffic problems – influence the health of the European population in a negative way. Some of these risk factors may be related to natural disasters (such as floods, erosion, fire and earthquakes). However the majority are man-made, and are either accidental (e.g. Chernobyl, the "Prestige" and BSE) or simply an outcome of our daily pattern of life and use of resources. However, it is difficult to quantify the extent to which exposure to environmental factors impacts on health, due to both a lack of reliable data and also the difficulty in identifying cause-andeffect relationships between environmental pollution and human health77. Graph 35 Urban air quality - ozone exposure above limit values - Average number of days of pollution exceeding standards for the air pollutant in urban areas 100 90 Changes in the way we live have affected our environment. In Europe more than two thirds of the total population now live in urban areas as a result of migration in the second half of the 20th century. Rapid urbanisation and urban decline have influenced the quality of life of the urban population adversely in many areas. Many cities have numerous districts with problems of poverty and social exclusion, very often combined with poor housing conditions. Facing urban decline during the 1980s, many cities responded with programmes for urban renewal and restructuring, in order to improve the quality of the urban environment and to support local economic and social regeneration. The major concerns in most cities regarding the environmental impact on health are air quality, noise levels, traffic accidents, and housing quality. ● 100 1998 1999 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 EU-15 IRL FIN P DK NL UK F B A D E I EL 0 Note: No data for Sweden and Luxembourg Source: Eurostat Major air pollutants in urban areas are sulphur dioxide, particulate matter, nitrogen oxides, carbon monoxide, lead, other heavy metals and organic compounds arising from various sources, such as heating, electricity generation, industrial activities and road traffic. Work has been carried out to reduce the levels of air pollution. Since 1980 all EU countries have reduced their emission of sulphur oxides on average by 70%, and similarly nitrogen emissions have fallen by 11%; however, carbon emissions have remained stable. ● Noise has become a problem in large cities, where the proportion of people exposed to unacceptable levels is two to three times higher than national averages. In addition to quality of life, noise also has an adverse impact upon health (sleeping disturbances and psychophysiological effects) and may also have an impact upon social behaviour (oral communication and work performance) and cognitive development (noise impairs children's learning capacity). On average, levels exceeding the maximum acceptable level of 65 dB(A) affect between 10% and 20% of inhabitants in western Europe and up to 50% in some cases in central and eastern Europe. ● Traffic issues are amongst the major environmental problems faced by cities, with private cars increasing their share in transport for a population living at increasing distances from their workplace. Increasing car traffic impacts on air pollution, noise levels and 77 This section is based on : European Environment Agency , Europe's Environment - The Dobris Assessment. 2001. http://www.eea.eu.int 59 Section 2 The social dimension of health ● Indoor air pollution is another important health risk. Indoor air pollutants are carbon monoxide and nitrogen dioxide generated by indoor combustion sources such as tobacco smoke, volatile organic compounds (e.g. from paints and cleaning agents) and asbestos fibres. The risk of lower respiratory tract disease in children exposed to tobacco smoke from parents smoking at home, is some 50% to 100% higher, and non-smokers who are married to smokers and exposed to tobacco smoke have a 20% to 30% higher risk of lung cancer. ● The main source of population exposure to ionising radiation lies in naturally occurring radon and its decay products. The populations most at risk are miners and residents of particular areas where radon is emitted naturally from the soil. Approximately two million people in Europe are estimated to be at elevated health risk from this cause. Recent studies from Finland, Norway and Sweden indicate that as many as 10% to 20% of all lung cancer cases in these countries can be attributed to residential radon exposure. For the EU it is estimated that up to 10,000 cancer deaths – or 1% of all cancer deaths – are caused annually by radon. ● Water and food contamination is a source of many communicable diseases and gastrointestinal diseases, such as hepatitis A and salmonella. Infrastructure has been developed to mitigate associated health risks and subsequently the volume of untreated wastewater has fallen, albeit unequally, across the EU - in 1970 levels exceeded 50m3 in some Member States, whereas they varied between nil and 30m3 at the end of the last decade. High incidence of hepatitis B and tuberculosis are observed in some countries (Romania, Bulgaria, the former USSR and Poland) and are partly related to lack of basic environmental conditions; for example, proper water sanitation and communal waste disposal. These factors may have the most pronounced impact on the occurrence of the communicable diseases in infants, and on infant mortality. Graph 36 Transport accidents by age (standardised death rates per 100,000), 1998 3,0 3,0 Male Female 2,5 2,5 2,0 2,0 1,5 1,5 1,0 1,0 0,5 0,5 0,0 0,0 0_4 10_14 20_24 30_34 40_44 50_54 60_64 70_74 80_84 Source: Eurostat Graph 37 Number of road traffic deaths per million population, 2001 0 20 40 60 80 100 120 140 160 180 200 60 63 66 UK S NL DK FIN D EU-15 IRL I 77 84 85 104 106 111 117 A E F B L EL P 129 137 143 144 178 184 0 20 40 60 80 100 120 140 160 180 200 B, I and UK: 2000 data from national sources. All 2001 data are estimates Source: CARE (Community Road Accident Database and Eurostat Demographic Statistics. the frequency of accidents. The social costs of deaths ('years of life lost') due to accidents for young people are very significant. The costs of a larger number of non-fatal injuries resulting from traffic accidents are also very high, involving temporary or permanent restrictions of human activity and disability. Subsequent impacts on health. ● Exposure to excessive levels of outdoor air pollutants may cause respiratory diseases, various allergies or increase the risk of cancers. It affects a large part of the European population and available evidence suggests that air pollutants are associated with 40,000150,000 adult deaths in Europe annually. Black smoke is considered to represent the biggest potential risk to health and could be the cause of 15% of asthma cases in Europe. Even low concentrations of suspended particles can provoke adverse health effects like heart and lung diseases. Another form of air pollutants is oxide of sulphur or nitrogen which may affect up to 30% of the European population. 2.2.4 The role of income and poverty Higher income is often related to better health. Income levels mediate the effect of social position on health status and income maintenance policies play an important role in this mediation process. Within countries there is a strong correlation between income and health, i.e. health improves with increased income levels. However, this link between income (or wealth) and health is, in most cases, not a linear relationship78: the increase in health from a fixed increase in income is smaller at higher income levels. The literature, however, reveals some cases where the relationship does 78 See M. Benzeval, K. Judge, "Income and health: the time dimension", Social Science & Medicine, (52), 2001. pp. 1371-1390. 60 The social dimension of health Section 2 seem to follow a more linear pattern, namely in Nordic Member States, where the income distribution may be considered to be more egalitarian and the social deprivation relatively smaller.79 Graph 38 Plotting self perceived health against income inequality in the EU Member States, 1998 Self perceived health “bad” or “very bad” in % of population 25 A study of 12 Member States examined the relationship between standardised disposable household income on the one hand and self reported health and chronic illness on the other80. A strong positive relationship between income and health appears to be evident in almost every country under consideration. Moreover, it is interesting to see that, in some countries such as the Netherlands, Portugal, France, Italy and Spain, the probability of reporting ill health is considerably higher in the lowest income quintile when compared to the next higher income quintile. There is a similar relationship between income and chronic illness where the likelihood of reporting chronic illness is higher in the lowest income quintile than in the next highest quintile in countries such as the Netherlands, Spain and Italy. Again, at least for the countries mentioned, the theoretical idea of 'investing in health where it is most effective' could be achieved by improving the income position of the poorest part of population, thereby most efficiently increasing overall health status. 25 P 20 20 D 15 15 I E UK 10 DK A 5 10 EL F B 5 NL IRL 0 0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 S80/S20 ratio (total income of the richest 20% of pop./total income of the poorest 20% of pop. Note: No data for L, S, FIN Source: ECHP - UDB, 12/2001 convincing82. However, this may be due to measurement problems – for example, the nature or size of the sample or the choice of the inequality coefficient. This notwithstanding, the fact remains that there are plausible pathways between social and economic deprivation and mortality or ill health. Furthermore, increased inequality implies that an increased segment of the population suffers from economic and social deprivation. In addition, inequalities with regard to health, at the individual level and across societies, are also linked to the extent that individuals receive social support and societies develop their social networks, which is discussed in detail in section 2.4. Despite long-term economic growth, increased levels of education and an increase in average per capita income, socio-economic health inequalities have widened in some countries. There are many ways to examine the possible source of this apparent paradox. For example, it might be possible to link this with relative (income inequality) or absolute (poverty) economic deprivation, which are addressed, in turn, in the following paragraphs. The impact of poverty on Health. There is no universally agreed definition of poverty nor is there general agreement on how to measure it83. However, the majority of researchers agree that poverty can be measured as the proportion of the population whose income is below a certain threshold. Poverty may, in general, be conceived to imply a lack of sufficient material resources available for daily living. It is known that it creates a vicious circle of ill health related to malnutrition, poor housing and insufficient sanitation and hygiene. Furthermore, it is often associated with exposure to environmental and other health risks which may result in mental health problems and drug abuse. In addition, poverty has been shown to increase the length of common mental disorders84. Health differences between different socio-economic groups are linked to income inequality. The graph below plots the S80/S20 ratio (the ratio of the richest quintile's total income to the income sum of the poorest quintile) against the percentage of the population who perceive their health to be "bad" or "very bad" for each Member State81. The concept of income inequality has sometimes been challenged. It has been argued that the evidence for an association between income inequality and health is less 79 Martikainen et al "Income differences in mortality: a register-based follow-up study of three million men and women", International journal of Epidemiology, (30), pp 1397-1405, 2001. Osler et al "Income inequality, individual income, and mortality in Danish Adults: analysis of pooled data from two cohort studies", British Medical Journal, (324) pp 1-4, 2002. It should be noted that these two studies carried out in relatively egalitarian societies report large income related mortality differences particularly among men, see S. Kooiker / J. Wildeboer Schut (Social and Cultural Planning Office, The Hague, Netherlands), "Income and health – a review of the literature and an empirical analysis", study carried out for the European Commission, DG Employment and Social Affairs (E/1), 2003, pp 6-7. 80 Kooiker/Wildeboer Schut, pp 22-26. 81 The correlation coefficient of the two variables is +0.46. 82 It is true that if the S80/S20 ratio is replaced by the Gini coefficient the correlation coefficient reduces to +0.26. Lynch et. al. have found evidence that existing associations between income inequality and health are largely limited to child health outcomes and decline with age. See Lynch, J. et. al., "Income inequality, the psychosocial environment, and health: comparisons of wealthy nations", Lancet, 2001 (358) pp. 194-200. 83 For example, the monetary poverty threshold is 60% of national median equivalised income. Other threshold or concepts may be chosen affordability of certain baskets of goods covering basic needs, dependency on social assistance, homelessness etc. Broader definitions also include non-material aspects of poverty like psychological problems, lack of social relations and lack of education. 84 Taken from Weich and Lewis "Poverty, unemployment, and common mental disorders: population based cohort study", British Medical Journal, (317:115-119). The study, which used British Household Panel Survey data for two consecutive years, found that where there was poverty and unemployment the mental illness would be more likely to still be present in the second year. Furthermore, current financial strain (a selfperceived indicator) was a better predictor of future psychiatric morbidity than either unemployment or poverty. 61 Section 2 The social dimension of health Graph 39 Plotting self perceived health against poverty in the EU Member States, 1998 25 3 3 Self-reported health Daily activity restrictions P 20 20 D 15 15 I E 10 F UK EL 10 A DK B 5 Odds ratio* Self perceived health “bad” or “very bad” in % of population 25 Graph 40 Relationship of self reported health and long-term poverty (4 consecutive years below poverty line of 60% of median income) 2 2 1 1 5 NL IRL 0 0 5 10 15 20 0 25 0 B Poverty Rate in percent (cut-off point: 60 % of median equivalised income). DK D EL E F IRL I NL A P UK Note: No data for L, S, FIN *For example, for self reported health: Relation of probabilities of reporting health ‘less than good’ being long-term poor to not being long-term poor. Source: ECHP - UDB, 12/2001 Source: Eurostat - ECHP 1995-1998 The impact of absolute deprivation on health has been investigated for more than a century. There is common agreement that a stable association between poverty an individual’s health condition exists - inequalities in health are almost always to the disadvantage of the poor. The graph above shows how poverty85 relates to self-perceived ill health86. is for a poor person compared to a non-poor person. As age and sex also have an impact on both health and long-term poverty, the coefficients in the graph have been controlled for these two variables. The values for self-reported health range from below 1 in Denmark89 to 2.8 in Portugal. In most of the countries considered the evidence that the poor are more concerned by ill health than the non-poor is weaker when considering restrictions in daily activities. The values here range from less than 1 in Denmark and Belgium to 2.2 in the Netherlands. In addition, poverty is a major source of stress and often a precursor to severe mental health problems. Compensatory abuse of tobacco, alcohol or other drugs is especially widespread among people in poverty, further accelerating their health problems. Fighting poverty is therefore a major health issue. When measuring the association between health status and poverty, it is important to give special consideration to long-term poverty, as the time dimension of poverty appears to be a particularly crucial determinant. It can be shown from a recent study that the relation between chronic illness and 'less than good' self-reported health on the one hand and poverty on the other hand becomes more significant with longer periods of poverty.90 In most of the Member States considered it is significantly more likely for a poor person to have bad health than for a non-poor person and, moreover, this gap in the likelihood of poverty further increases if poverty has existed for more than four consecutive years. In other words, poorer health status is associated particularly with long-term poverty. However, the findings shown in the two graphs above have to be interpreted with caution. As seen in those graphs, the respective relations become considerably weaker if Portugal and Germany are excluded. Irrespective of their income position, Germans and the Portuguese tend to think more negatively about their health than people in the other Member States considered. In fact, it appears that in these two countries the share of those people perceiving their health 'less than good' within the non-poor is larger than the corresponding share even within the poor in the other Member States87. The evidence that ill health is considerably more widespread among the poor than among the non-poor varies strongly among Member States. This is illustrated in the following graph, which shows the association between long-term poverty88 and poor health by means of two indicators: self reported health (as used above) and activity restrictions. The height of the bars indicates how much higher the probability of feeling ill In addition to long-term poverty considerations, another important time dimension is health and income dynamics over time. Considering the two health variables 'self reported health' and 'chronic illness' it appears that, within a period of four consecutive years, changes in health status were not significantly related to income drops. However, taking a longer period into account 85 86 87 88 Measured in terms of the OECD threshold of 60% of national median equivalised income. The correlation coefficient for these two variables is +0.42. See S. Kooiker / J. Wildeboer Schut, p. 21 A person is considered to be amongst the long-term poor if their income is below 60% of national median income for at least four consecutive years. 89 The figures below 1 in Belgium and Denmark have to be treated with particular care and must be seen in light of the fact that these coefficients are not significant at the 5 % level. This is also true in the case of daily activity restrictions in Ireland, Austria and the UK. 90 S. Kooiker / J. Wildeboer Schut, p 27-28. 62 The social dimension of health Section 2 health) plotted against "poor" housing conditions which is measured by the share of households reporting three or more housing problems93. It is important to interpret data with caution: some of the housing problems may be less of an issue in some Member States for example, the lack of central heating would be less of a problem in Portugal than in Finland94. could well lead to a different result91. This illustrates the cumulative impact of socio-economic determinants on health discussed above. 2.2.5. The impact of housing Housing conditions can affect health directly and indirectly. Many studies have been devoted to the link between housing conditions and health.95 However, finding empirical evidence for the thesis that bad housing conditions cause ill health is not straightforward as other factors influence health, and highlighting one specific housing aspect as a root cause is rather difficult. For example, the findings, on whether overcrowding has a negative impact on health condition, are ambiguous.96 The association between health and overcrowding is actually influenced by factors such as time spent at home, other housing and living conditions, cultural diversity among cohabitants and, of course, income. However, even facing these statistical problems, there is some evidence linking overcrowding with mental symptoms, like depression. Furthermore, clear empirical evidence has been found to link poor housing conditions to the ill health of children97 - for example, lead water pipes have a negative impact on the neurological development of children. Empirical results attribute the highest health risks to cold, damp and mouldy housing conditions where the strongest link appears to be between reported illness in children on the one hand and dampness and mould on the other hand. Furthermore, the cold significantly contributes to increasing death figures in winter. Housing conditions can also be used to characterise the relative level of social deprivation, using indicators such as ownership or renting, size and sanitary installations. Housing, therefore, becomes an element of socio-economic status and is, of course, closely associated to income and wealth. It is obvious that bad housing conditions regularly coincide with poverty and promote ill health as there are direct links between the quality of a person's dwelling and health status. These links include poor sanitary conditions, temperature, humidity, insufficient ventilation, noise and insufficient space. Such conditions may promote communicable diseases, allergic sensitivity and physical and psychological discomfort. Furthermore, there are also indirect relationships: lack of social cohesion creating tensions among cohabitants which may lead to isolation and social exclusion. It can be seen, therefore, that poor housing clearly impacts on health92. Graph 41 Plotting self perceived health against housing conditions in the EU Member States, 1998 25 Self perceived health “bad” or “very bad” in % of population 25 P 20 20 15 15 2.2.6. 10 Poor nutrition is one of the major causes of morbidity and mortality… I The role of lifestyle E 10 EL F A B DK 5 5 NL IRL Inadequate nutrition – i.e. a poor overall dietary pattern – has important consequences in socio-economic terms, contributing to health deficiencies or resulting in economic and social costs. Swedish analysis has shown that in the EU almost 10% of the disabilityadjusted life years are lost due to poor nutrition (4.5%), obesity (3.7%) or inactivity (1.4%)98. Recent decades have brought about considerable changes in how much people spend on food: the share of house- 0 0 5 10 15 20 25 30 35 40 45 Share of households reporting three or more housing problems Note: No data for L, S, FIN. Source: ECHP - UDB, 12/2001 A wide variety of indicators exist for housing conditions. The graph above shows ill health (the share of the population with self-perceived "bad" or "very bad" 91 Kooiker/Wildeboer Schut (2003), p28. 92 World Health Organization (1998) "Housing is fundamental to physical, mental and social well-being and quality of life" In World Health Report 1998 - Life in the 21st century: A vision for all. Geneva: WHO. 93 The problems included are: SPACE (Lack of space), NOISE (Noise from neighbours or outside), DARKNESS, HEATING (inadequate heating facilities), POLLUTION (Pollution caused by traffic or industry), DAMP (Rot in the house or damp or leaky roof), CRIME (Vandalism or crime) 94 As expected, there is a very strong positive correlation between these two measures (correlation coefficient: +0.92). However, due to a lack of data, countries that are important for this analysis, like Germany and the UK, are not included. 95 An overview of the results of this research is given by D. Wilkinson (Housing Research Branch), "Poor Housing and Ill Health – A Summary of Research Evidence", The Scottish Office, Central Research Unit, 1999. The following paragraph is quoted from this paper (among others). 96 See also AHURI (Australian Housing and Urban Research Institute), "Do housing conditions impact on health inequalities between Australia’s rich and poor?", April 2001. This study concludes with results that are contrary to those expected. 97 See also A. Jackson and P. Roberts, "Physical Housing Conditions and the Well-Being of Children", Canadian Council on Social Development, Ottawa, March 2001. 98 Determinants of the burden of disease in the European Union. Stockholm, National Institute of Public Health, 1997. 63 Section 2 The social dimension of health hold budgets used on food has halved, to 25%. Also, more food is consumed away from the home, prevailing traditions based on supply and season have become globalised and the dietary differences between various parts of Europe have reduced99. Graph 42 Obesity incidence, % of population who are severely overweight (BMI = 30+) 14 14 12 12 Male Female 10 There are two forms of malnutrition: under-nutrition and over-nutrition. The former may be either insufficient intake of energy/protein rich food, as is often the case in many developing countries, or alternatively insufficient intake of nutrients (minerals or vitamins) which is more common in Europe. Over-nutrition, on the other hand, is linked with an excessive intake of energy rich food, which is often deficient in nutrients100. Dietary habits that are especially threatening to health are characterised by the consumption of quantitatively enough food of low nutritional value. 10 8 8 6 6 4 4 2 2 0 EL UK P B FIN L EU 15 DK NL E IRL A I F D S 0 Source: Eurostat - Key data on Health 2000. Furthermore, it is also noteworthy that diseases which to some extent are of a dietary origin, or are aggravated by poor nutrition, like cardiovascular diseases, diabetes, cancers, osteoporosis and arthritis, are particularly prevalent among older people. With the ageing of the population in Europe these diseases are likely to increasingly dominate the overall health pattern of the population. Therefore, preventive actions, promoting adequate nutrition policies, will become very important. At its meeting in early December 2002 the Council of the European Union therefore underlined "the need, in preventing and responding to the problems resulting from obesity, to take a cross-sectoral approach, including, the health, social, food, educational, cultural and transport sectors." Furthermore, it invited the Commission to develop innovative measures concerning nutrition and physical activity and to ensure that the prevention of obesity is mainstreamed in all relevant Community policies, particularly the new framework programme concerning public health (2003-2008). Obesity. Being overweight or obese increases the risk of some chronic diseases. For instance, cardiovascular diseases (in particular ischaemic diseases and hypertension), certain cancers and diabetes type 2 increase considerably with a Body Mass Index (BMI)101 between 27 and 30 (overweight), and very rapidly with a BMI of 30 or over (severe obesity). A study by the Institute for European Food Studies suggests that around 30% of EU adults are overweight (between 24% to 35% depending on country) and around 10% are obese. The data held by Eurostat shows slightly lower rates: 17% of EU citizens have a BMI between 27 and 30 while 6.5% have a BMI of 30 or over. A recent study102 based upon American data showed that in terms of longevity the optimal BMI was approximately 23-25. There appeared to be a J-sloped relation between being overweight and years of life lost for any given age category - lower for older adults than for younger people - with the maximum number of years of life lost being 13 for 20-30 year old very obese men (BMI>45) and 8 years for women. Abuse of alcohol, tobacco and illegal drugs As discussed in Section 2.1, alcohol, tobacco and drug abuse represent additional serious health risks. They lead to accidents and violence, which can have fatal outcomes, and are exacerbated by problematic social conditions. However, use of alcohol, tobacco and drugs is not necessarily linked to socio-economic status, but, like nutritional insufficiency, will accentuate existing health risks. In the long term they are likely to trigger heart diseases and certain cancers. Obesity appears to be on the increase, particularly in children, in all countries where data is available. This fact produces concerns for the future and obesity is now regarded to be one of the fastest growing epidemics. It has been estimated that approximately 30% of cardiovascular diseases are related to unbalanced nutrition, and that obesity accounted for around 7% of the total health care budget in some member states. The large number of deaths attributable to cardiovascular diseases and cancers, and how these high death rates are linked with diet, is discussed in Section 2.1 of this report. Tobacco use is associated with a vast array of, sometimes fatal, diseases that may otherwise have been avoided, such as heart diseases and pulmonary diseases. The Swedish analysis referred to above also found that dis- 99 However, the forthcoming enlargement will include countries where the dietary habits are characterised by a relatively high intake of fats. 100 The recommended daily dietary intake in most EU countries varies between 2200 and 2900 kcal per capita, of which fats should not exceed one third. In fact, the average dietary intake exceeds the recommended threshold in all EU states (3413 kcal on average in 1997) and the fats account for almost 40% with relatively stronger increases over the last three decades in the "Mediterranean" countries. 101 Overweight and obesity is measured by a 'body mass index' (BMI) calculated as the body weight (kg) divided by the squared height (m). 102 Journal of American Medical Association vol 289 N°2 of the 8th January 2003. 64 The social dimension of health Section 2 However, if the psychological and socio-economic circumstances are conducive, and if drugs are readily available, drug use may be prolonged and intensified. Use of illegal substances is concentrated amongst young adults, especially men in urban settings. The prevalence rate among young adults is roughly twice that of all adults. Surveys also suggest that young people are more likely to have been recently offered drugs than older adults. Graph 43 Proportion of the population who declare they smoke regularly 60 60 Male Female 50 50 Total 40 40 30 30 20 20 10 10 0 Throughout the EU cannabis is the most common illegal drug. Cannabis use increased throughout the 1990s in most EU countries, particularly among young people. Around 10% to 30% of European adults state they have tried cannabis at least once and recent use is reported from 1% to 10%. 0 B DK D EL E F IRL I L NL A P FIN S UK EU 15 Source: Eurobarometer - June 2000 (EU-15) Amphetamines have been tried by 1% to 6% of the population, cocaine and ecstasy by 0.5% to 4.5%, and heroin by less than 1% of Europeans. Recent use of amphetamines, cocaine and ecstasy is reported by less than 1% of adults on average. Graph 44 Proportion of the population who declare they smoke regularly 60 50 50 40 40 30 30 20 20 10 10 0 BU CY CZ EE HU LT LV MT PL RO SI SK Graph 45 Relative number of acute drug-related deaths recorded in EU countries in 1999 Number per 100,000 population 60 0 TU CC13 EU15 Source: Eurobarometer - August 2002 (CC 13) ability adjusted life expectancy was reduced by 9% in the EU due to tobacco smoking. The smoking prevalence among women, particularly young women, has increased since the 1980s against a declining prevalence among men. Overall, one third of the EU(15) population declare that they smoke regularly, a figure similar to that reported in the acceding States. Smoking prevalence among men remains higher than for women, both in the EU(15) (40% for men and 28% for women) and in the acceding States (48% for men and 23% for women)103. 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 UK DK FIN L P EL IRL D I A S E NL F Note: Data from different countries are not directly comparable as there are differences in case definition and recording methods. Source: EMCDDA Drug use presents challenges for all Member States in terms of social, health and criminal justice policies. Problematic drug abuse is associated with wider indicators of social disadvantage such as unemployment, poverty, homelessness and social exclusion, and is also correlated with delinquency and criminality. Substance abuse adversely affects physical and mental health. Mental disorders, particularly depression, are prevalent among substance abusers and also in early experimenters105. In the case of injecting drug users, communicable diseases such as HIV and Hepatitis C are a cause for concern. Drug related deaths, mainly from accidents, violence, overdoses and suicides, are a further issue. Around 7,000 to 8,000 acute drug-related deaths are reported each year in the EU, although the real number is probably higher106. According to surveys, one European in five aged 15-64 has tried an illegal drug at some point104. The figures for recent use (in last 12 months) and current use (in last month) are lower, at 7% and 4%, while around 0.5% of the population are deemed to be problematic drug abusers. The statistics suggest that many people who take illegal drugs do so experimentally or intermittently. Indications are that initial and irregular drug use is linked to curiosity, opportunity and peer group behaviour. 103 Eurobarometer: EU(15) June 2000; CC(13) August 2002. 104 EMCDDA-European Monitoring Centre for Drugs and Drug addiction, 2002: Drugs in Focus: Measuring Prevalence and Incidence of Drug Use & Annual Report on the State of the Drugs Problem in the European Union and Norway. 105 DG Health and Consumer Protection, 2002, Report on the State of Young People's Health in the European Union. 106 EMCDDA, 2002, Annual Report on the State of the Drugs Problem in the European Union and Norway. 65 Section 2 The social dimension of health common, there is evidence that new HIV infections in younger age groups continue to rise as the overall proportion of people living with HIV/AIDS falls. Graph 46 Number of births per 10,000 births, where the mother is between 15 and 19 years old, by Member State, 2000 40 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 Regular physical exercise has positive impacts on health. Physically inactive people run a substantially higher risk of contracting diseases compared to moderately and highly active people. It has been estimated that eliminating physical inactivity would result in 15% to 39% less coronary heart disease, 33% less strokes, 12% less hypertension, 12% to 35% less incidences of diabetes, 22% to 33% less colon cancer, 5% to 12% less breast cancer and 18% less osteoporosis related fractures. A Finnish estimate of the impact of physical activity on the use of hospital services showed that most active men spent 36% and most active women 23% fewer days in hospital than the least active people. 0 0 DK D EL E F IRL I L NL A P FIN S UK Note: 1999 data for D, EL, E, F; 1996 for I. Source: Eurostat The EU has developed a global, multidisciplinary and integrated Action Plan on Drugs (2000-2004) to fight drug supply and demand107. Strategies have been developed to combat drug trafficking and target drug-related crime, alongside measures to educate and prevent drug use, and to tackle social exclusion more generally. The reduction of drug-related health damage, through education, prescription of substitution drugs and provision of sterile injecting equipment, has become a new objective in the co-operation between Member States. Recent evidence indicates that health benefits are also accrued through intermittent daily activity of moderate intensity. Health-enhancing physical activity (HEPA) includes many physical activities related to lifestyle, not only during leisure time but also at work and in the home. A survey by the National Public Health Institute of Finland shows that the level of leisure-time physical activity has increased steadily in the 20 years since the survey began in 1978. However, walking and cycling to and from work decreased steadily. Particular issues faced by young people. The risks of infection by sexually transmitted diseases (including HIV and AIDS), unintended pregnancy and abortion are significant issues in young people's health. At the onset of their sexual life, many young people lack knowledge or skills in order to protect themselves, and use of health services and supplies (such as condoms) by young people is often inadequate. Furthermore, young people's sexual relations are frequently sporadic or unplanned, which can increase exposure to health risks. Graph 46 shows the number of births per 10,000 births, where the mother is between 15 and 19 years old, by Member State. The Pan-EU Survey of Consumer Attitudes to Physical Activity, Body-weight and Health, carried out in 1999108 provides comparable activity patterns across the 15 Member States. In this survey, exercise for at least 3.5 hours per week was considered beneficial to health. On average 41% of the population were insufficiently active to benefit health, although the percentages varied widely from 14% (Finland) to 70% (Portugal). Also, on average, women were found to participate less and for shorter periods than men, and the likelihood of exercising for more than 3.5 hours decreases with age, while people with higher levels of education were more active than those with lower levels. Sexually transmitted diseases (STDs) are a major health problem with far-reaching health, social and economic consequences. Problems associated with STDs include serious complications (such as infertility and long-term illness) and lengthy or costly treatments. AIDS poses a particular threat as an incurable and debilitating disease. European research suggests that for young people chlamydia is the most common STD, with a prevalence rate of 5% to 7% within this age group. Although less Physical activity has recently become more prominent on the health agenda. In most countries, physical activity plays an important role in health promotion and disease prevention. This is manifested in local or regional physical activity projects or other measures aimed at promoting active lifestyles. 107 European Commission, 1999, Communication from the Commission to the Council and European Parliament on a European Action Plan to Combat Drugs (2000-2004) 108 http://www.iefs.org/ 66 The social dimension of health Section 2 2.2.7. The role of socio-economic determinants and the link with social policy and contribute to later health deficiencies (see Table 4)110. Similarly, stressful work conditions in adult life may influence behaviour and generate health deficiencies, occupational diseases or injuries. It is, therefore, important to highlight the dynamic nature of the link between socio-economic factors and health. From the analysis contained within this section it becomes clear that health status109 is determined, to a large extent, by the physical and the socio-economic environment. Factors such as educational level, occupation, working conditions and levels of income and wealth represent key determinants which influence the distribution of social and material resources among people. They also critically determine the exposure to health risks and therefore explain most of the observed health inequalities. Addressing issues related to the major determinants of health provides further potential for promoting health and preventing disease. It has been shown111 that public policies, which, over longer periods, aimed to create employment, promote inclusion and improve the distribution of educational and social security resources, had a positive macro-impact upon the population's health status (longevity, mortality). These considerations were among the focus points of the European Social Policy Agenda112, adopted in 2000 at Nice, with the central aim to promote quality as the driving force for building a thriving economy and an inclusive society with more and better jobs. Long-term effects on health may also occur as a result of the accumulated impact of different factors over long periods of exposure to detrimental socio-economic conditions. For instance, the combination of variations in income and employment status may create economic hardships, particularly at lower income levels, which gradually impact on physical and psychological health 109 "Health is a state of complete physical, social and mental well-being, and not merely the absence of disease or infirmity. Health is a resource for everyday life, not the object of living. It is a positive concept emphasising social and personal resources as well as physical capabilities". (WHO) 110 The diagram is adapted from J.Lynch and G.Kaplan "Socio-economic position." In L.Berkman & I.Kawachi (eds) Social Epidemiology. Oxford University Press, 2000: chapter 2. It shows how socioeconomic position can have an impact throughout the life course and create sequential and cumulative - both positive or negative - health impacts at individual level. 111 Prof V.Navarro, e.a.: Social Capital, Income Inequalities and Health, European Commission, DG Employment and Social Affairs, 2003. Correlations found in this study demonstrate the impact of redistributive public policies in improving health of the entire population –in particular, in decreasing infant mortality. It therefore suggests that, in order to improve the health of a population, it is far more effective to develop universal programmes that reduce inequalities than to develop programs specifically targeted at reducing poverty. 112 COM(2000) 379. 67 Table 4 The impact of socio-economic position on health throughout a life course Impact (+ or -) Determinant Maternal lifestyle Nutrition Pre-natal health care Birth Weight Growth Cognitive capacity Socio-economic position (digest., respic. defic.) Social environment Household status Education Networking Childhood Diet (obesity, diabet) Exercise Confidence building Social/physical maturing (e.g. artherosclerosis, mental disorders) Continued education Social status Work conditions (control) Occupational function Hierarchical position Adulthood Employment/unemployment Nature of job (precarity) Job related stress factors Life style (drugs, tobacco) (e.g. cardiovascular and pulmonar diseases, cancers) Income and wealth (assets) Social status Household status Old age Control of living conditions Network and social support Social protection (e.g. functional disabilities) The social dimension of health Section 2 2.3. Healthcare systems in Europe ● The specific way a healthcare system is organised, funded and utilised is highly relevant for health outcomes. It is also important to focus on the quality of health care systems in conjunction with the extent to which they are accessible for those in need. Despite the fact that universal, or near universal, rights to health care are found in every Member State, these do not automatically lead to universal access. Thus, although access to healthcare has increased significantly over recent decades due to Member States' efforts, differences in coverage still persist across Member States. In fact, there are problems of access associated with various gaps in coverage. These problems arise in two ways: as a consequence of the exclusion of particular treatments from statutory health insurance coverage, or as a consequence of increasing reliance on user charges. ● With respect to quality of care, Member States have made significant efforts to improve the quality of structures, processes and outcomes in healthcare. Most have made considerable progress in establishing standards to assure high levels of quality health care. However, this has proved to be difficult in certain areas, for example with outpatients, and in relation to the introduction of outcome-related standards. Pressure to improve the quality of care experienced by patients has continued to grow, as have pressures to contain costs. Increasing awareness that spending on inefficient technologies imposes opportunity costs on services has contributed to an increase in the demand for evidence on the budgetary impact and cost-effectiveness of interventions as part of health technology assessment. Quality evaluation of healthcare delivery can be found in one form or another in all EU countries. ● The problems with recruitment and retention of medical personnel, which are already being felt in some Member States, are likely to be accentuated by the overall trend towards an ageing and shrinking workforce and both trends could increase costs. Thus, the health sector will have to adjust to the impact of ageing on its personnel as well as on its clientele. Shortages of health staff due to ageing will present healthcare with a difficult challenge and this is particularly true for nurses. In five Member States almost one in two nurses are already over 45 and in a further seven Member States 40% of nurses have reached this age. Two other factors contribute markedly to the shortages of nurses: stop-go trends in recruiting policies and demanding working conditions coupled with moderate pay leading to a high staff turnover. ● Policy makers will also have to address the rising expectations from health care consumers. Changes in lifestyles, patterns of work, incomes, educational levels and family structures are altering people's attitudes towards healthcare. Changing attitudes include increased awareness of patients' rights and responsibilities, less tolerance of discrimination and less deference towards health care professionals. Evidence indicates that people desire greater choice, more individualised services and access to a wider range of medical treatments – including those beyond the traditional boundaries of health care systems. ● Total healthcare expenditure as a proportion of Gross Domestic Product is presently highest in Germany, followed by France and Belgium. In the case of Germany, this is due to a high emphasis on hospitalisation and by far the highest EU propensity to consult both general practitioners and medical specialists. In many Member States, referrals from GPs are required for specialist treatment and such gate-keeping systems may contribute to a below-average propensity to consult specialists in these countries. In most Member States, a considerable share of total health care expenditure has to be paid directly by users as a consequence of gaps in insurance coverage for specific products and services. This is particularly true for the southern Member States, where the share of out-of-pocket payments as a proportion of total health expenditure is highest. ● Long-term care is often divided between various different public structures and budgets – normally between the health budget and the budget for social services. However, long-term care costs within the health system are often difficult to distinguish from the cost of more traditional health interventions and, furthermore, social services are mostly provided at local level. For these reasons it is sometimes difficult to establish both costs and national trends. 69 Section 2 The social dimension of health ● The weight of the health sector in the economy is considerable. On EU-15 average, employment in the health and social services is almost 10% of overall employment. Moreover, the health sector is a very dynamic sector with substantial potential for contributing further to economic growth and employment. ● All acceding States, except Malta, spend a lower proportion of Gross Domestic Product on health care than the EU average. There appears to be a relatively high propensity to use hospital services in the acceding States mainly as a result of underdeveloped primary care. However, in many of these countries there are fewer medical staff per inhabitant and the hospital infrastructure and other health care facilities are relatively poor. Freedom of movement associated with the accession of these countries imposes further challenges to the provision of treatment and services, as medical staff may be attracted by higher wages in the current EU countries. Limitations on working hours, due to the extension of the European Union Working Time Directive towards the acceding States, may have similar effects. There is a certain trend towards privatisation of health care provision in a number of the acceding States. This is accompanied by more private resources being devoted to health, mainly through out-of-pocket and informal payments. Introduction be differences in their individual ability to fully benefit from services, which are related to socio-economic status, age, gender and ethnicity. Special measures may be needed to maintain full access for all, as population ageing will increase the demand for health services and long term care. Looking at factors combating ill health, the health care system becomes the key determinant in health outcomes. Many diseases, which were previously fatal, are now being treated successfully using new methods and medicines. In this sense health care systems have made very direct contributions to the recent rise in longevity113. Since morbidity tends to rise with age, access to quality health care is likely to be of greater importance to health outcomes for older people than for the young114. With the ageing of European societies an increase in the relative importance of health care in the overall health of the population is therefore to be expected. 2.3.1. The quality of health care is not only a question of the level of funding, but also depends on the way health care is organised. The relative emphasis on primary, secondary and tertiary care, and the integration of these services, may be significant to health outcomes. The capacity for early intervention and for careful follow-up of treatments may also have an impact. Sensitivity to the way that differences in lifestyle and living and working conditions can influence the need for medical treatment is an important consideration. As circumstances are subject to change, adaptability is also a feature of quality. Demographic change, new epidemiological patterns, medical progress and increased demand for medical treatments are likely to affect the way healthcare is delivered. The key issues of accessibility, quality and sustainability Across Europe, there are differences in the way health care systems are organised, financed and utilised. Yet there are also many similarities in the problems that healthcare systems have to tackle, with population ageing standing out as a particularly pertinent example. The European Commission has pinpointed accessibility, quality and sustainability as three key issues in the future of healthcare systems. Forthcoming demographic developments will be a major challenge to the financial sustainability of healthcare systems. Changes to the organisation and financing of healthcare, in order to help contain rising costs whilst maintaining full access to high quality services, will be a universal aim. All Member States offer equal access to public health care for people residing in their territory, but there may 113 Estimates have suggested that the political transition in Eastern Germany and Poland, bringing about changes in in the health care systems, were associated with improvements in life expectancy. See Nolte, E. et al, "The contribution of medical care to changing life expectancy in Germany and Poland". Social Science and Medicine 2002; 55:pp1905-1921 114 However, even at older ages the impact of health care systems on health outcomes can be easily overshadowed by other factors. Life expectancy and the perceived quality of health differ among the Member States, irrespective of the sums they spend on health care. For example, health care expenditure in Germany amounted to 10.3% of Gross Domestic Product (GDP) in 1999 compared to 7.0% in Spain, although the average life expectancy in Germany was one year shorter for men and two years for women than in Spain. 70 The social dimension of health Section 2 2.3.2. Achieving universal access and high quality in the EU Member States Graph 47 Percentage of the population covered by the statutory health system in the EU, 1960 and 1997. Countries with differentiation between Inpatient (IP) and Outpatient (OP) coverage Universal, or near universal, rights to health care can be found in every Member State. However, universal rights do not automatically ensure universal access. In recognition of existing barriers to access in the health care systems of many Member States, and in support of EUwide action to remove such barriers, the European Commission recently proposed the achievement of universal access to health care as an objective of health care systems in the EU and a priority objective for EU co-operation in social protection115. The Commission’s proposal formalised efforts already made by some Member States in this direction. 100 100 Population coverage in % 1960 1997 80 80 60 60 40 40 20 20 0 0 IP OP Belgium IP OP Finland IP OP Greece IP OP Ireland IP OP Luxemb. IP OP Netherl. Source: OECD, 2001 Barriers to access stem from both health service supply and demand. On the supply side, factors such as service availability and distribution, the location of health services and the existence of waiting times for treatment all affect access. On the demand side, an individual's income, age, knowledge, beliefs, information, preferences and opportunity costs are likely to influence their use of health services. Whether the healthcare system eases or reinforces such inequalities in access on the demand side depends on how healthcare delivery is organised and paid for. Some of the initiatives applied in attempts to contain costs and raise quality may have less fortunate effects on the achievement of access objectives. Graph 48 Percentage of the population covered by the statutory health system in the EU, 1960 and 1997. Countries with statistics on total population coverage 1960 1997 100 80 80 60 60 40 40 20 20 0 0 A In order to realise the objective of reasonably immediate access for all, over the last decade, many Member States took initiatives aimed at reducing waiting times. Several Member States enshrined the rights of patients in law (Finland, Greece, Denmark and the Netherlands) or used tools to promote patients' rights (France, Ireland, Portugal and the UK). The introduction of such legislation provides a framework for protecting the needs of previously excluded social groups, but in itself does not guarantee full equality of access. The introduction of universal coverage in France is perhaps the most significant recent attempt to increase access to health care in the EU. France now joins Denmark, Finland, Greece, Ireland, Italy, Luxembourg, Portugal, Sweden and the UK in providing universal statutory health coverage116. Near universal coverage can be found in Austria (99%), Belgium (99%) and Spain (99.8%). The graphs below show the increase in levels of coverage in all Member States since 1960. 100 DK F D P E S UK I Source: OECD, 2001 treatments and pharmaceuticals, which are either fully or partially excluded from coverage. In almost all Member States patients must make out-of-pocket payments for such services, or purchase complementary Voluntary Health Insurance (VHI) to cover these costs117. It is important here to consider the links and occasional trade off between access and quality considerations. When quality is raised it may take quite a while before it becomes possible to secure access for all to the higher quality services. Deficiencies and inequalities in access to health services are also an important quality issue. It is crucial to take access and equity considerations into account when developing quality standards. Reaching an optimum between access and quality concerns is likely to necessitate action across more policy areas and involve a number of actors. In many Member States central government only creates framework legislation, while the more detailed design and implementation of services are left to regional or local level. In spite of the official achievement of universal or near universal statutory health insurance, problems of access persist in some areas. This is particularly true for dental 115 European Commission 1999; European Commission 2001. 116 OECD 2001. 117 E Mossialos and S Thomson. Voluntary Health Insurance in the European Union. Report prepared for Directorate General for Employment and Social Affairs. 2002. Brussels: European Commission. 71 Section 2 The social dimension of health Quality in health care naturally concerns structures and processes as well as outcomes. Quality criteria for structures are concerned with aspects such as the training and experience of staff and the use and condition of equipment and buildings, where binding standards set by public bodies will often apply. Quality criteria for processes are connected with the treatment itself and how specific services are carried out. Formal guidelines are being developed in many Member States but at present, they are less prevalent than those concerning structures. Measuring quality in final health outcomes is quite demanding. Quality criteria here may focus on positive indicators like healing and survival rates or on negative ones, such as complications during a specific treatment. So far only a few Member States apply this approach to quality evaluation. However, the cost of health care gives this quality requirement a new dimension. Given the limitation of resources, it appears to be difficult to ascertain high quality of medication and treatment. This is particularly true in the light of the wide variety of patterns of provision of health care services described later in this section and the disparity of medical treatment. Therefore, cost and quality are inexorably linked and establish the focal point of a more comprehensive quality improvement approach. Many studies have shown that quality improvement policies, particularly within the secondary sector, make it possible to reduce the cost resulting from poor quality care. 2.3.3. The growing interest in quality issues has led Member States to create specific institutions or bodies responsible for promoting quality work, running assessments and developing guidelines or accreditation systems. Such central bodies now exist in almost all Member States. Cross-border mobility of healthcare services.119 Although the total share of health care spending due to claims for reimbursement of cross-border health care is still very low120, cross-border mobility of patients is expected to increase in the light of the Union's eastward enlargement. Moreover, the aspect of universal access to national healthcare systems is closely linked to the question of free movement of health services across the internal borders of the Union. One noteworthy trend in Member States’ responses is a focus on the role of patients. In nearly all countries efforts have been made to introduce measures to safeguard the rights of patients, in particular in the hospital sector. Empowering patients to take informed decisions and providing adequate and unmediated information and transparency about health services, treatment options and access to medical records are important aspects in this context. For example, there are now specific patients’ rights laws in Austria, Finland and Denmark. In the area of healthcare, the principal of free movement of services, which is laid down in the Amsterdam Treaty, is associated with an important dilemma referring to the possible cost/quality trade-off mentioned in the previous section and the relation between the basic Treaty principle and the special nature of public health insurance and healthcare. Price agreements with domestic providers, rationing and waiting list are important tools used to support health cost containment in some Member States. Hence providing citizens with the right to frequent services of higher capacity and quality, but also of higher cost, in a neighbouring Member State represents a new and serious cost driver for the first country. The collective citizens and state interest in keeping heath care affordable and controllable could therefore be in contradiction with the obvious interest of individual citizens suffering from an illness to get the best possible treatment as soon as possible. Access and quality naturally have cost implications and these objectives must be achieved within the overall framework of financial sustainability, which in turn is highly dependent on the funding and organisation of health care systems. Ensuring value for money and cost containment are also important objectives in relation to healthcare. There may be important trade-offs between access and quality on one hand and cost containment on the other. Yet these objectives may also be pursued in tandem in mutually reinforcing ways. If the wider societal cost is considered it may, for example, be cheaper to extend health coverage to everybody than to suffer the consequences of fragmented coverage in terms of human capital losses and the higher cost of late interventions118. In addition, many studies have shown that quality improvement policies, particularly in the hospital sector, can make it possible to reduce the healthcare and wider societal cost resulting from poor quality care. On the other hand, optimal resource allocation could call for commercial providers to be allowed to sell their services across borders and thus to compete with providers in other Member States. Using this argument, it does make sense to use excess capacity and allow citizens to seek out the best services. 118 The US Kaiser Commission on Medicaid and the Uninsured: "Sicker and Poorer: The Consequences of Being Uninsured", May 2002. 119 The subsequent comments are partly based on Vandenbroucke, Frank, "The EU and Social Protection: What should the European Convention Propose ?", Paper presented at the Max Planck Institute for the Study of Societies, Köln, June 17, 2002. 120 It ranges between 0.1 and 0.2 percent of overall public spending on healthcare, see Busse, R., "Border-crossing patients in the EU", Eurohealth, Vol 8, No 4, Special Issue Autumn 2002, p. 19. 72 The social dimension of health Section 2 The overall effect of increasing mobility of healthcare services on health quality outcomes is also far from clear: ● The resulting enhancement of international competition among providers of services may help increase the quality of services. For example, excess capacity in one Member State may help mitigate problems of long waiting lists in another. Moreover, quality might be positively influenced by the possibility to establish international centres of excellence for specific treatments. Cross border co-operations will be facilitated. ● Additional pressure on prices for services due to increased competition may affect quality inversely. Increased efforts in monitoring healthcare services across borders will be necessary due to asymmetric distribution of information between the home country's insurance institution and another country's healthcare provider. For instance, the controlling of bills issued abroad for specific treatments will be very difficult for the home country's National Insurance institution. Recently, efforts aimed at increasing patient mobility through better access to healthcare systems across the Union have been stepped up. This is also true at a local level; several regions divided by borders between Member States have included healthcare service arrangements partly to ease the administrative burden for patients crossing the border within these regions123. At EU-level the Barcelona Summit of March 2002 gave a green light to the Mobility Action Plan to remove obstacles within the European labour markets by 2005. As a consequence, the EU Commission has suggested that all EU citizens be issued with a European Health Insurance Card replacing the forms that insured people presently need to take with them when they are staying temporarily in another EU country. The idea is not to give rise to new care entitlements but to facilitate reimbursement by the home country if people fall ill while visiting another Member State. 2.3.4. The basic Treaty principle, of free cross border movement of services, is also problematic from the legal point of view as it mainly relates to economic activities. One could consider whether healthcare services should be viewed more as a 'solidarity' issue rather than an 'economic' one, and therefore largely to be exempt from the freedom of movement principle. Indeed, much of the legal conflict and judgements of the European Court of Justice (ECJ) is about this distinction. The variety of healthcare systems in the EU There is a wide diversity among Member States in the way healthcare systems are organised, regulated, financed, delivered and utilised. This makes it difficult to model the differences in a single typology. In other words, the clustering of countries according to the way systems are financed does not coincide with the clustering according to modes of organisation, regulation or delivery. Moreover, the distinguishing features of healthcare provision may differ markedly from the way social protection is organised in other fields such as pensions. The emphasis on universal tax-financed healthcare in, for example, the UK and Denmark stands in marked contrast to the emphasis given to occupational and private provisions in the pension system. At present, regulation 1408/71 from 1971121 provides the mechanism for co-ordination of national social security legislation in order to protect the social security rights of people moving within the European Union. In the case of healthcare services, this means that it protects patients receiving medical services or treatments in another Member State as long as they have authorisation from their national healthcare insurer. Graph 49 Cluster plot of funding sources (taxation against social insurance), by Member State Percentage of total health expenditure from social health insurance However, there is evidence that healthcare services should be subject to free movement of services according to the Treaty. In addition to public not-for profit provision, there are several healthcare service providers and health insurance institutions which are commercial in nature and operate within a market-based framework subject to competition. Moreover, a recent ruling from the European Court of Justice, which forces national healthcare insurers to reimburse citizens for healthcare service expenditure incurred beyond national frontiers without prior authorisation, suggests that healthcare may not be considered as exempt from the free-movement rule122. 100 100 80 80 F NL 60 D 60 A 40 EL 40 B 20 P 0 0 20 40 20 S FIN 60 IRL I UK S DK 80 0 100 Percentage of total health expenditure from taxation Source: OECD Health Data 2001. 121 Council Regulation (EEC) No 1408/71 of 14 June 1971 on the application of social security schemes to employed persons and their families moving within the Community. 122 The Kohll and Decker rulings should be mentioned here (ECJ, Kohll, C-158/96, (1998) ECR I-1931 and ECJ, Decker, C-120/95, (1998) ECR I-1831). 123 Busse, R. (2002), p. 20-21. 73 Section 2 The social dimension of health The graph above illustrates how Member States cluster according to the relative role of general taxation and earmarked health insurance contributions in the overall financing of health costs. Number of consultations of medical specialists Graph 50 Number of consultations of general practitioners and of medical specialists (last 12 months) per Member State, 1998* The proportion of total health expenditure from social health insurance and from taxation is indicated respectively by the y-axis and the x-axis while the distance from the diagonal indicates the proportion from private sources. Some of the other main differences between Member States, notably those within the organisation, delivery and utilisation of healthcare are brought to light when broader distributions between and within the primary, the secondary and the tertiary care sector are examined in detail. 3,5 3,5 D 3 3 2,5 2,5 L A F 2 FIN B EU 2 E NL EL 1,5 UK 1,5 I P 1 1 DK IRL 0,5 0,5 0 0 1 2 3 4 5 6 Number of consultation of general practitioners Note: *ECHP-UDB2001, except EU, D, I 1996; F, FIN 2000. Source: Eurostat, except France CREDES and Finland STAKES. The high number of specialist consultations in Germany, Belgium and Luxembourg can partly be explained by the fact that general practitioners in these countries do not act as gatekeepers to specialist treatment. In other words, the possibility of consulting a specialist directly in these countries undoubtedly increases demand for specialist services. Moreover, the distinction between primary care doctors and specialists has become blurred, so that many specialist-trained physicians also provide primary care services. For example, in Germany – the country with the highest number of consultations with both general ractitioners and specialists – about 60% of office-based physicians are specialists124, who often provide primary care services as well as speciality services. The primary care system. The differences between primary care systems become evident when the input factors are examined, such as the number of physicians and patterns of utilisation indicated by the number of consultations with general practitioners (GPs) and specialists across the Member States. The number of physicians per 100,000 inhabitants varies within a ratio of nearly one to three among Member States: Italy has close to 600 physicians per 100,000 inhabitants, while Ireland and UK have close to 200 physicians per 100,000 inhabitants. In most countries with a lower than average propensity to consult medical specialists (Denmark, Ireland, Italy, the Netherlands, Portugal, Spain and the UK), referrals from general practitioners are required in order to access specialist treatment, which certainly limits the number of consultations with specialists. In these countries specialist and general practitioner consultations are complements rather than substitutes. With the exception of Italy, the countries mentioned also experience a below average propensity to consult general practitioners. This suggests that, in these countries, a relatively low propensity to consult general practitioners is also reflected in the low propensity for specialist consultation. In Belgium, France, Austria and Finland around half of all physicians are general practitioners, while in Spain, Ireland, Italy, the Netherlands, Portugal and Sweden over 80% are medical specialists. Data on the proportion of physicians working in hospitals is available for nine Member States. In France and Italy this comes to less than one third, suggesting an emphasis on primary care sector provision. In contrast, more than two thirds of physicians work in the hospital sector in Denmark, Portugal and the UK. There are wide variations in the number of consultations with general practitioners and medical specialists within the primary care system. At one end, Germany has the highest number of consultations with both general practitioners and medical specialists, with an average of 8.4 consultations per person per year. Austria and Belgium are also at this end of the spectrum, mainly due to the high numbers of consultations with general practitioners. In contrast, the UK, Ireland, Denmark, Portugal and Greece figures are about half those of Germany. Finland, France, the Netherlands and Luxembourg are close to the European Union average for consultations with medical specialists but below the EU average when it comes to GP consultations. For the countries in the upper right corner of the previous graph, (Germany, Belgium and Austria) which experience higher than average general practitioner and specialist consultations, this 'complementary explanation' applies only to Austria where general practitioners also function as gatekeepers to specialist consultations. However, in Belgium and Germany people can contact specialists directly without referral. Therefore, there is not necessarily a complementary relationship between the number of consultations with general practitioners and specialists in these countries. 124 US GAO, 1993. 74 The social dimension of health Section 2 The secondary care system. Again there is variation between Member States within an approximate range of one to fifteen; in the UK the average length is 6 days, compared to 96 days in Greece. Within the secondary sector – the hospital in-patient care system – differences between Member States are even wider. The propensity to hospitalise people is illustrated by the number of discharges of hospital inpatients, where the ratio between the high Austrian figure and the low Portuguese figure is three to one. The propensity to retain in-patients within the care system is illustrated by the 'average in-patient length of stay', where the ratio between the German level and the Irish level is two to one. Both of these indicators are shown in the graph below. The EU average for the number of in-patient days for mental and behavioural disorders per 100,000 inhabitants lies at 13,000, although it varies significantly between Member States. While some Member States still place emphasis on hospitalisation others have long sought to handle people with less serious mental and behavioural disorders outside the institutional medical system, in order to avoid their social exclusion. Mental and behavioural disorders still account for one tenth of the EU average number of in-patient days. Scope for cost-containing reductions in the use of hospitalisation is narrow in Denmark and the UK, where mental disorders only account for 1 in 67 in-patient days. However, it would seem to be considerable in other Member States, such as Greece, Sweden and Spain, where mental disorders account for one in every four, in every five and every seven days spent in hospital respectively. Graph 51 Number of hospital discharges per 100,000 inhabitants and average in-patient length of stay against the EU average, 1998 150 Average number of in-patients days 150 140 140 D 130 FIN SK 120 SI EL 110 NL E HU CZ CA F 70 DK US 60 IRL 50 50 100 If one-day hospital stays and mental and behavioural disorders are excluded, the general contrast between heavy hospitalisation and light hospitalisation systems is confirmed. Austria has the highest rate of hospitalisation, followed by Finland, the UK and Germany, with values at least one third above the European average. A second group, with Belgium, Luxembourg, Italy, Denmark and Greece, has values ranging from close to the EU average to 75% of the EU average. A third group, which includes all remaining Member States, has values of approximately two thirds of the EU average. It is worth noting that the countries where one-day hospitalisation is most developed do not belong to the heavy hospitalisation group. In the Netherlands 60% of all hospital discharges were one-day cases by 2000, whereas in 1993 the corresponding figure was 35%. Having pursued cost-containing policies in this area from 1991 onwards, Denmark, and Sweden also have high rates of one-day hospital treatment. At the other extreme, rates in Germany were as low as 5% in 1999. 80 L 70 0 100 90 S 80 60 UK I P 120 110 100 90 A EU B 130 150 50 200 Hospital discharges per 100,000 inhabitants Note: EU average number of discharges per 100,000 inhabitants=17260 (=index 100), EU average in-patient length of stay = 8,5 days (= index 100), EL, F 1997; HU 1999 Source: Eurostat. Multiplying the two indicators discussed ('number of hospital discharges' and 'average in-patient stay') gives the number of hospital days per 100,000 inhabitants and here the ratio between the outliers is four to one. At one extreme, Finland combines a very high propensity to hospitalise people with a lengthy retention of inpatients, resulting in an average 'days in hospital ratio' that is twice the EU-average. Similarly, Germany, Austria and the UK can be said to be systems of high hospitalisation, with a total number of hospital days one third above the EU average. In such cases, cost-containing policies appear to have been unsuccessful. At the other end, Portugal, Ireland, France and the Netherlands, and to a more limited extent Spain, Denmark and Sweden, show low propensities to hospitalise and/or to retain inpatients. These systems are more similar to the US and Canadian patterns, where the number of hospital days lie well below the EU average. Graph 52 Number of nights of in-patients in hospital, 1998* 180 If in-patient care due to mental and behavioural disorders is examined the diversity among Member States is particularly large. The number of discharges per 100,000 inhabitants for mental and behavioural disorders varies within a ratio of one to fifteen, with 116 discharges per 100,000 inhabitants in Portugal, and 1,787 in Finland. Germany and Austria, along with Sweden and Luxembourg, show high propensities to hospitalise people with mental and behavioural disorders. The average length of stay in hospitals for mental and behavioural disorders in the EU was 24 days in 1998, although this number is declining. Index 100 = average EU-15 (134,000 in-patient nights per 100,000 inhabitants) 180 160 160 140 140 120 120 100 100 80 80 60 60 40 40 20 20 0 0 P NL E IRL S F EL DK I L B D UK FIN A EU 15 SI Note: Mental and behavioural disorders excluded; *UK only England Source: Eurostat 75 SK CA US Section 2 The social dimension of health Graph 53 Hospital beds per 100,000 inhabitants, 1990-2000* 1500 1500 1990 2000 1200 1200 900 900 600 600 300 300 0 EU15 S UK E DK NL P IRL I EL L A B FIN F D TR US NO PL SI CH EE HU LV LT CZ JP 0 Note: *Except 1990-99 for EU-15, DK, E, EL, IRL, I, L, P, CH, JP and 1992-2000 for S; (Data for Sweden only considered after the coditication change of 1991-92) Source: Eurostat Even when general practitioners act as gatekeepers for the secondary care system, as is the case in many Member States, the pressures of demand are greatest in the secondary care system. In some Member States (Spain, Portugal and Ireland) hospital emergency departments also allow direct access to the secondary care system, or allow patients to bypass waiting lists. EU average (with 23 and 30 beds per 100,000 inhabitants in Italy and Spain respectively). This is either because living with relatives is common, as in Spain, or because institutionalisation of elderly people is less acceptable. Graph 54 Number of long term care beds per 100,000 inhabitants, 1990-2000* The number of hospital beds is another supply side indicator. The number of beds per 100,000 inhabitants varies greatly between Member States. In Germany and Austria there is a clear correlation between the number of beds and the number of in-patient nights in hospital. France has a similarly high ratio, but the occupation rate of hospital beds there is the lowest in the EU, with less than four months average occupation in the year, compared to an EU average of eight months. Conversely, the UK shows a low number of beds, but these are occupied virtually all the time, as they are in Finland and Austria. The trend in the number of beds is clearly downward, with an average decrease of 20% over the 1990s in almost all countries considered. This trend is illustrated by the graph above. 1200 1200 1999 2000 1000 1000 800 800 600 600 400 400 200 200 0 B DK D EL E F IRL I L NL A UK NO CH CZ EE HU LT JP 0 Note: *Except L: 1993; NL, A: 1994; UK: 1996; EL: 1997; IRL: 1998; DK, I: 1999 Source: Eurostat The tertiary care system. In the tertiary care system the relative amount of resources devoted to institutionalisation varies considerably between Member States. Paradoxically, in Denmark, which has a clear priority on providing services and care to older people in their own home, more beds are devoted to long term nursing care (725 per 100,000 inhabitants, excluding psychiatric beds) than to normal hospital care (494 per 100,000 inhabitants). The Eurostat 1995 household-based scenario projects that the proportion of the population aged over-80 in 'institutional households' will reach 10% by 2010, with high values of 24% for the Netherlands, 19% for Ireland, and low values of 4% in Spain, Portugal and Sweden. The percentage in this age group, of 'persons living alone' is projected to lie at an average of 45% across the EU, with values below 32% in Spain and Portugal, and above 60% in Sweden and Denmark. Ireland, the UK and Germany have between 350 and 550 beds per 100,000 inhabitants, with Germany having raised the number of long-term beds by a factor of three over the last decade. After reforms in the early 1990s, Sweden has moved most of these beds out of the health system and into social services. Belgium and France show figures that are below the EU average (between 135 and 75 beds per 100,000 inhabitants). The Mediterranean Member States are also well below the The WHO European Health Report 2002 (p. 116) stresses that the previously rigid boundaries between primary and other forms of care are gradually becoming blurred. This development brings about the definition of common goals across all care sectors. It also leads to the necessity of improved service management and coordination in order to successfully bypass or substitute for hospitalisation and in patient care . 76 The social dimension of health Section 2 2.3.5 healthcare expenditure with serious diseases. On the other hand, if the individual cost of specific treatments decreases due to modern technology, this leads – and should lead – to increased access to these treatments, which in turn might increase demand and overall cost. Public expectations and healthcare expenditure. Changes in the age structure of the population and in medical technology and treatments are well recognised as potential cost drivers in healthcare. However, policy makers concerned about cost containment will also have to address the new structural trend of rising expectations. Changes in lifestyle, work patterns, income, educational level and family structure are altering people's attitudes towards healthcare. Consumerism, global travel and the internet have increased and facilitated access to a wide range of information on health topics. Technological progress in healthcare also impacts on people's attitudes about the services expected from healthcare institutions. It is hard to find examples of new technologies that have reduced spending in the health system as a whole, rather than on individual patients because so far, there has been relatively little research on the overall effects of introducing new technologies on healthcare systems. Studies of specific procedures or diseases indicate that the impact of technology varies by disease and by procedure. Health Technology Assessment. As new technologies, including pharmaceuticals, medical devices, diagnostic procedures and delivery mechanisms, are continually introduced health authorities have an acute interest in assessing the cost effectiveness and wider consequences of technological change in the health sector. Changing attitudes includes increased awareness of patients' rights and responsibilities, less tolerance of discrimination on the basis of age, gender, religion or ethnicity and less deference towards healthcare professionals (particularly doctors). There is widespread evidence of a desire for greater choice and more individualised services, greater accessibility and convenience in light of increased working hours, and for access to a wider range of medical treatments – including those beyond the traditional boundaries of healthcare systems. Throughout the EU, there has been substantial, albeit uneven, growth in Health Technology Assessment (HTA) activity during the last decade125. Beginning with the Swedish agency SBU in 1987, there are now more than 20 organisations in the EU that are members of the International Network for Health Technology Assessment (INAHTA), producing more than 150 reports annually. Most of these HTA bodies have an advisory role, although some do play a role in reimbursement and coverage decisions. Assessment can take many forms - it may consider clinical effectiveness only, or other wider dimensions such as socio-economic impact. New technology and healthcare expenditure. At present, the overall impact of new technology on healthcare costs is not clear. Although previous persistent rises in healthcare expenditure are often attributed to ‘technology’ – especially as demographic pressure has not previously been a factor – our knowledge of how technology affects healthcare costs is limited. Several Member States, including Finland, Ireland, the Netherlands, Portugal, Sweden and the UK (England & Wales), now have, or are in the process of developing, mandatory requirements for economic assessment. Elsewhere the submission of economic evidence as part of an evaluation is an increasingly important, but voluntary, requirement, for example in Denmark, France, Germany, Italy and Spain126. New technologies should, in theory, lower the cost of providing healthcare, either through reducing lengths of stay in hospital or saving specialists’ costs. However, technological change may contribute to rising healthcare expenditure, either as a result of the intensity of use of existing technology or the introduction of new technologies. Technologies can also be resource intensive and cost increasing if they require additional skills or organisational changes, or if they expand the range of treatments available but lead to only minor improvements in effectiveness. Moreover, it is often stated that technological progress in the health sector increases health costs by creating its own demand. Once medical technologies and innovative treatments have been developed, there might, on one hand, be the ethical obligation to make use of these resources, particularly by people concerned The increase in healthcare evaluation reflects common social and economic forces. Pressures to improve the 'quality' of care experienced by patients have continued to grow. Furthermore, pressures to contain total costs, coupled with increasing awareness that spending on inefficient technologies imposes opportunity costs on other patients, have driven an increase in the demand for evidence on the budgetary impact and cost-effectiveness of interventions. 125 McDaid D, Cookson R. Evaluating healthcare interventions in the European Union. Health Policy. [Vol/No and yr] Also, Banta D, Oortwijn W. (eds) Special section on health technology assessment in the European Union. International Journal of Technology Assessment in healthcare. 2000; 16(2): 299-638 126 Cookson R, Maynard A, McDaid D, Sassi F, Sheldon T, eds. Analysis of the Scientific and Technical Evaluation of healthcare Interventions in the European Union. Report to European Commission, July 2000. pp 1- 251. Updated May 2001. London. London School of Economics and Political Science. Available from http://www.lse.ac.uk/Depts/lsehsc/astec_report.htm. 77 Section 2 The social dimension of health In many Member States structures are now in place for the production of high quality HTA. However, translation of evidence into practice will ultimately depend on the development of structures to encourage dissemination, incentives to promote use and monitoring systems to encourage compliance with evidence-based guidance. The challenge is to build and refine these systems. the stabilisation of healthcare expenditure as a percentage of GDP, in some EU Member States, may not reflect success in controlling growth in healthcare expenditure, but rather reflect economic growth. For example, healthcare expenditure in Ireland grew by 3.4% from 1995 to 1998 and the economy grew by 8.8%. In Finland and Sweden, healthcare expenditure actually declined. For Sweden, the decline is due to the combined effect of severe cost-containing policies and of the shift of expenditures from healthcare budgets to social service budgets. Severe economic recession in Finland resulted in large-scale cuts in expenditure, especially public expenditure. On the whole, in 1999 the share of health expenditures in GDP varied between 10.3% in Germany and 6.1% in Luxembourg, with a weighted average of 8.4%. Trends in healthcare expenditure In the 1960s and early 1970s welfare spending in the largest OECD countries rapidly increased. During the mid and late 1970s, a combination of economic recession and the growing burden of unemployment cast doubt on the belief that increased welfare spending was sustainable. In fact, overall welfare state spending has stabilised in many Member States. However, healthcare expenditure has continued to rise in real terms. Graph 56 Total healthcare expenditure as a percentage of GDP, 1990-1999 International comparisons of health expenditure data present several methodological problems. These include organisational differences between health and social care systems, standardising definitions across Member States and different methods of data collection. healthcare expenditure data should thus be interpreted with some caution. Nevertheless, data shows that per capita healthcare expenditure continued to grow through the 1980s and 1990s in most EU Member States, though not at the rates seen during the 1970s. Public expenditure on healthcare also continued to grow, especially in Germany, Ireland, the Netherlands, and the UK, where public expenditure on healthcare grew faster than total expenditure. 12 2500 2000 2000 1500 1500 1000 1000 500 500 EL E F IRL I L NL A P FIN S 8 7 7 6 6 5 5 4 4 3 3 2 2 1 EU15 B DK D EL E F IRL I L NL A P FIN S UK 0 Note: *1999 except EL, E, D, IRL, P: 1998 Source: OECD Health Data 2001 healthcare expenditure can be broken down according to the areas of healthcare on which money is spent. One key element in healthcare expenditure, and one that receives much of the attention in expenditure control, is hospital costs. Hospital costs in the EU, as a percentage of total healthcare costs, have remained fairly stable since the 1980s. Data shows that the hospital sector accounts for over 40% of total expenditure on health in twelve of the fifteen Member States. However, the share of hospital costs varies between 31% and 61% of total healthcare costs. Despite efforts in many Member States to increase the role of primary care, the relative costs of secondary and tertiary hospital care remain predominant. 1990 1999* 2500 D 9 8 0 3000 DK 10 9 Expenditure by sector 3000 EU15 B 11 10 1 Graph 55 Health expenditure per capita (PPP), 1990-1999* 0 12 1990 1999* 11 UK 0 Note: *1999 except EL, E, D, IRL, P, S: 1998 Source: OECD Health Data 2001 Pharmaceutical expenditure has also grown as a percentage of total expenditure, however, it is still below 20% of total health expenditure, except in France, Portugal, Spain and Italy. The different indicators may suggest an over-consumption of drugs in France: in terms of the number of units of medicines per person. Using the indicator of drugs purchased in retail pharmacies, France shows figures per capita at one third above the average of Germany, Italy, the UK and Spain, but still at three During the 1990s, average total health expenditure as a percentage of Gross Domestic Product (GDP), stabilised in most EU Member States. Only Germany, Greece and Luxembourg reached their peak value in the second half of the 1990s. GDP, however, grew faster than healthcare expenditure between 1995 and 1998 in eight of the 15 EU Member States, and in four others healthcare expenditure grew only slightly more than GDP. Thus, 78 The social dimension of health Section 2 quarters of the USA level. The indicators of total pharmaceutical expenditure per capita in terms of purchasing power parity (PPP) show similar variations, notwithstanding the fact that the proportion of the French population consuming prescription free medicines or vitamins lies slightly below the EU average. This suggests that the high consumption of medicines could be mainly driven by the health system itself. health contribute to healthcare revenue in France and Italy. At least part of the tax revenue from the sale of cigarettes has been earmarked for healthcare in Belgium and the UK. Tax revenue is also used to subsidise or make transfers to social insurance funds. Tax funds may be transferred into insurance funds to cover the contributions of the non-employed population, preventing the fragmentation of coverage. The non-employed population may be given the same entitlement as the working population and are able to access the same providers, so that solidarity is maintained across the population. This would also prevent the duplication of administrative and purchasing functions. Furthermore, taxes may be used to cover the deficits of insurance funds. This can prevent year-on-year increases in contribution rates and thereby avoid increases in labour costs of the contributing employees. On the other hand, if insurers do not carry the risk of deficit they will have no incentive to contain costs or to operate efficiently. Some Member States do not declare the tax transfers to social health insurance whilst others make these explicit in national accounts. Sources of funding Healthcare systems in Europe rely on a mix of funding sources. Most funding in all Member States is public expenditure raised through taxation and social health insurance contributions. Except in Greece, Italy and Portugal, private expenditure (from private insurance and out-of-pocket payments) accounts for less than 30% of total health expenditure. The graph shows the percentage of total health expenditure from public sources, with the complement coming from private source, in 1990 and 1998. Out-of-pocket payments or user charges constitute a supplementary form of finance, which may be used under all of the three main funding types. Social health insurance. Graph 57 Public expenditure as a percentage of total expenditure on healthcare, 1990-1998* 100 1990 1998* 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 0 One of the defining features of social health insurance is the requirement to have an independent system of revenue collection distinct from government – otherwise it could be considered as an earmarked payroll tax. The collection agent can be a single social insurance fund (Belgium), or may be devolved to independent funds (France), individual health insurance funds, either occupationally or geographically defined (Austria, Germany) or an association of insurance funds (Luxembourg). Social health insurance contributions are the predominant source of finance in France, Germany, Luxembourg, whilst the Netherlands. Austria, Belgium and Greece have dual systems with approximately equal proportions funded from taxation and social health insurance. 100 10 EU15 B DK D EL E F IRL I L NL A P FIN S UK 0 Note: *Except D: 1997 Source: OECD Health Data 2001 Some reform proposals in the late 1980s and 1990s sought to introduce competition between social health insurers. In theory, a system of competing public insurers offers enhanced choice, can reduce contribution rates and improve quality. However, there may be problems of 'cherry picking' or adverse selection, which could concentrate risks in certain funds and differentiate the contribution rates. The motivations behind attempts to introduce insurer competition in Germany and the Netherlands were specifically financial, including increasing the efficiency of insurers, reducing variation in contribution rates and reducing the level of contribution rates or at least reducing any increases, rather than to increase subscriber choice. As statutory insurers are obliged to accept nearly all applicants for insurance, competition between funds requires a mechanism for adjusting for risk to stop some insurers from bearing a disproportionate part of the risk or adopting covert forms of 'cherry picking'. The public/private mix in healthcare funding has implications for the distribution outcome. International comparisons consistently confirm that healthcare systems that rely substantially on private funding are more regressive in their distribution effects than those in which funding is predominantly public. Taxation Taxation plays a role in the funding of health services in nearly all European countries. It is the predominant source of revenue in Finland, Denmark, Ireland, Italy, Portugal, Spain, Sweden and the UK. Of these, regional and/or local taxes are the main source of revenue for healthcare in Denmark, Finland and Sweden and also, since 2000, in Italy. National taxes are the main source of revenue in Greece, Portugal, Spain and the UK. Hypothecated or earmarked income taxes for 79 Section 2 The social dimension of health Private health insurance. Graph 58 Out-of-pocket payments as a percentage of total expenditure on health, 1990-1998* The early development of mutual and voluntary benefit associations in Europe, and their subsequent transformation into national health insurance funds, has generally only left a residual role for private health insurance. The role of voluntary health insurance in the EU can be classified as substitutive, supplementary or complementary. In a few Member States private insurance substitutes for public coverage for certain segments of the population. Complementary health insurance enables access to services that are not available under the public insurance systems (a top-up policy) or cover user charges, while supplementary insurance offers increased consumer choice and access to better quality services, or simply allows quicker access to standard services. Obviously, private health insurance is likely to enhance inequalities in access to healthcare. 50 50 1990 1998* 40 40 30 30 20 20 10 10 0 EU15 B DK D EL E F IRL I L NL A P FIN UK 0 Note: *Except B: 1996; E, D, I, L, P: 1997 Source: OECD Health Data 2001 1990s and in 1998 the EU-average was 16%. In most Member States, out-of-pocket payments constitute a more significant part of health expenditure than private health insurance benefits. As illustrated in the graph above, the proportion of out-of-pocket payments is highest in the Mediterranean Member States, and remains around or below 10% in six Member States. Voluntary health insurance (VHI) in Member States can then be distinguished further according to how premiums are calculated (risk, group or community rated), how benefits are determined and the status of the insurance providers (for-profit or not-for-profit). Where private health insurance substitutes for statutory or public insurance, as in Germany and the Netherlands, individuals with high incomes are covered. As income is related to the risk of ill health, separating public and private insurance according to income concentrates people at a higher risk of ill health within the public system. This undermines the redistributive effect of the funding arrangements. The agents collecting private health insurance premiums can be independent private bodies, such as private for-profit insurance companies (in most countries that have a private health insurance market), private not-for-profit insurance companies or funds. While out-of-pocket payments may be a significant extra source of finance, their primary function is usually that of curbing demand. User charges (co-payments rather than direct payments) are employed in all Member States to control pharmaceutical spending. Although most healthcare in the EU is publicly funded, this is not the case in the pharmaceutical sector, where levels of private expenditure are high in many Member States. Pharmaceutical expenditure is predominantly privately funded in Belgium, Finland, Greece and Italy. In Denmark it is equally shared between private and public funding. Furthermore, in recent years the share of public funding has been reduced in several Member States, largely in an attempt to contain healthcare costs. Between 1980 and 1997 the public share of total expenditure on pharmaceuticals declined in nine out of the fifteen Member States. The decline was small in Sweden, the Netherlands, Portugal and the UK, but substantial in Italy and Belgium. In contrast, a few Member States saw some increase in the share of public funding for pharmaceuticals, with a significant increase in Ireland. Private health insurance may be subsidised through tax credits or tax relief, as in Austria, Ireland and Portugal. Germany and the Netherlands have limited tax relief, which does not particularly offer an incentive to purchase policies from private providers as the same restricted relief also applies to social security contributions. Belgium, Denmark, Finland, France, Spain, Sweden and the UK do not offer tax relief on private health insurance. Transaction costs tend to be higher under private health insurance due to administrative costs related to billing, contracting, utilisation review and marketing127. Extensive administrative work is required to assess risk, set premiums, design complex benefit packages and review and pay or refuse claims. Consumer information problems are also associated with defining benefits and setting premiums. In addition to co-payments for pharmaceuticals, every Member State makes use of co-payments to control spending on dental care. Some Member States have also introduced co-payments to contain the costs of ambulatory and inpatient services (for example, Austria, Belgium, Finland, France, Ireland, Luxembourg and Sweden), either by raising existing charges or introducing charges for services previously provided free of charge. Out-of-pocket payments The share of out-of-pocket payments within overall EU health expenditure increased slightly during the 127 It has been argued that ‘hidden’ transaction costs for the patient, such as long waiting times, may in fact be higher in publicly funded systems (Danzon and American Enterprise Institute for Public Policy Research 1994). 80 The social dimension of health Section 2 Member States generally use three types of co-payment: flat-rate payments that are fixed fees per service, coinsurance based on a percentage of the total cost, and deductibles, which require the user to bear a fixed quantity of the cost. Deductibles may be reduced over time. Graph 59 Share of health related expenditure in individual consumption expenditure per thousands 70 60 The co-payment can vary depending on drug groupings, as in France, Greece, Italy and Portugal, or on drug pack size, as in Germany, while a flat rate is charged for all drugs in the UK and Austria. In Belgium, Greece, France, Luxembourg, Portugal and Spain the patient pays a fixed proportion of the cost. Deductibles are used in Denmark, Finland and Sweden. 70 1994 1999 60 50 50 40 40 30 30 20 20 10 10 0 EU15 B DK D EL E F IRL I L NL A P FIN S UK 0 Source: Eurostat - Household Budget Survey. Significant population groups are exempt from co-payments in many Member States, which limits the impact of user charges as a means of containing healthcare costs or as a revenue-generating measure. Exemptions may reduce this regressive nature of co-payments if they are means tested. However, if exemptions are based on factors other than income, such as age or disease, they may result in horizontal inequity. Austria, Belgium, Denmark, Finland, Germany, Ireland and Sweden have introduced income protection schemes by setting an annual ceiling on co-payments for some services. Not all Member States exempt children from co-payments for preventive dental care. Denmark, Ireland and Spain exempt chronically ill people from pharmaceutical copayments. out-of-pocket-payments in Austria (decrease) and Finland (increase) is also not reflected by the development of the share of health in total consumption between 1994 and 1999. However, the graph also shows that, among the countries where 1999 data is also given, only Greece, Italy, Luxembourg and Sweden experienced considerable changes (increases) of relative health expenditure during the 5 years considered. The two previous graphs shown also indicate that, proportionally, more private resources have to be devoted to healthcare in countries with income levels below the EU average, such as Greece, Italy and Portugal. One of the reasons may be that the elasticity of health achievements with respect to income may be low in these countries. That means that people have to devote a greater share of their income, to achieve a given level of service or treatment, than people in other countries. Whereas user charges or out-of-pocket payments may be efficient instruments in strategies of cost-containment and/or strategies to generate the extra funds needed for a rise in the quality of services, they are likely to have adverse effects on the objective of full, equal access for all. Depending on their size and use they may enhance social inequalities in access and thus tend to reinforce existing patterns of inequality in health. A relatively high share of financing through out-ofpocket payments may also be associated with low levels of health insurance benefits and/or low levels of official remuneration of health sector personnel. In fact this may lead to the emergence of an unofficial grey or black system of supplementary fees, which must be paid in order to receive services of full standard quality. The trend in the level of out-of-pocket payments as a percentage of total expenditure in the 1990s is only partly reflected by the proportion of consumption expenditure that is devoted to health, according to the European Household Budget Survey128 as shown in the following graph. 2.3.6. Funding long-term care.129 In 2000, for ten countries with data available, total public expenditure on long-term care as a share of GDP ranged between 0.7% (France, Ireland and Austria) and about 3% (Sweden and Denmark). Considerable increases are to be expected until 2050. For the Netherlands, Sweden and Denmark the per capita increases of longterm care expenditure as a percentage of GDP are The graph shows that Belgium and France have a share of health related expenditure in consumption considerably higher than the EU average. However, this cannot be explained by relatively high out-of-pocket-payments in the two countries, since the share of this component in total health expenditure is below EU average. Considering the trend in the 1990s, the development of 128 The Eurostat Household Budget Survey shows the overall structure of consumption expenditure by detailed COICOP (Classification of Individual Consumption by Purpose) level. First level COICOP classification on health expenditure is (1) Medical products, appliances and equipment, (2) outpatient services and (3) hospital services. 129 Information for this section taken from: a) Wittenberg, R., Becky, S. and Knapp, M., "Funding long-term care: the public and private options", in:Mossialos et. al., "Funding healthcare: options for Europe, Buckingham and Philadeplhia, 2002; b) MISSOC (Mutual Information System on Social Protection in the EU Member States and the EEA), Social Protection in the Member States in the EU Member States and the European Economic Area, Situation on January 1st 2001 and Evolution. 81 Section 2 The social dimension of health expected to exceed two percentage points during the next five decades whereas France and Italy will experience increases of about half a percentage point.130 financed long-term care benefit system of the Federal Government and the Länder. In the UK there is a non-contributory, state-financed system providing cash benefits and benefits in kind for elderly or disabled persons and their carers. General taxation is the main source of funding for health services. Central and local taxation fund social services, which are mostly subject to user charges. The funding of long-term care in the UK was reformed in 1993 to increase localisation; local bodies were given the responsibility for assessing care needs and arranging care. Aside from technological development and changing family structures, a further challenge for financing longterm care systems in EU Member States is ageing. Demand challenges may be exacerbated by supply challenges due to the shrinking workforce and the associated greater competition for scarce labour between various sectors. It may therefore prove increasingly difficult to base the running of long-term care services on low-waged and low-skilled labour. In order to maintain an adequate supply of labour the remuneration, training and status of personnel may have to be increased and this could become a cost driver in its own right. Both the demand and the supply challenges have to be taken into account in organisation and funding approaches to long-term care. In most Member States a compulsory, contribution based, social insurance scheme is applied. In some cases a tax financed supplementary social assistance system is run for those in need, who are not covered by the insurance schemes. This is the case in Belgium, Spain and Germany. In Germany, a specific long-term care insurance was introduced in 1995. Since then, employees and pensioners are subject to compulsory, contributions based, long-term care insurance. Before this introduction, the social security system did not cover long-term care in Germany – individuals paid the cost subject to a means-tested social assistance safety net. Throughout Europe unpaid spouses and family members provide the bulk of long-term care. Beyond such informal care the funding of long-term care services varies greatly across the Union. Long-term care is often divided between various different public structures and budgets, notably between the health budget and the budget for social services. Consequently, in many Member States there is no separate scheme for longterm care; this is the case in Belgium, Greece, Spain, France, Italy, Finland and the UK. In some Member States long-term care elements are covered by an insurance system. This is true for Belgium, Germany, Greece, Spain, France, Ireland, Luxembourg, the Netherlands and Portugal. Some countries have their main funding source as general taxation (Denmark, Finland, Sweden, the UK and Austria). 2.3.7. Resource allocation and payment systems Resource allocation. In the majority of Member States the responsibility for administration of healthcare has, to some extent, been devolved to a local level. As this has been done to differing levels between Member States, the ability of each government to impact the system of resource allocation is not the same across the EU. In some cases, the central government has maintained a large capacity to impose trade-offs and regulations, as was formally the case with National Health Systems. But whenever regional delegation is developed, either on the revenue collection side or on the resource allocation side, the extent of State control may be reduced. On the other hand, the dependence on State subsidies may reduce the autonomy at the local level. Here, the EU landscape again shows clear variety in the regulatory institutions, and reforms towards more regional or local autonomy are being discussed in some Member States. The health insurance system in France covers the nursing component of care in long-stay sections of hospitals and in retirement homes funded by social contribution. A similar approach is applied in the Netherlands, where health services are funded by social health insurance for most of the population. However, an 'exceptional cost' element to the health insurance system covers nursing homes and community health services (but not residential care and home care). This special fund for long-term care services in the Netherlands is based on tax-related contributions supplemented by central government financing. Long-term care social services are often provided at local level. Sweden, for example, transferred responsibility for long-term care for elderly and disabled people to the municipalities in 1992. A similar change was introduced in Denmark at the same time. Denmark applies a universal scheme, funding health and social services through general taxation: Local taxation finances most long-term care services. Similarly, in Finland long-term care services are financed by local authorities, as part of healthcare and social services. Austria applies a tax The devolved purchasers or plans can be a local government (as in Sweden), a local administrative body (as in Portugal), or a sickness fund (as in Germany, Belgium and the Netherlands). The functions of revenue collection and purchasing are usually separated and there are mechanisms for allocating money from the national level to the devolved purchasers. Even where devolved funds are responsible for collecting revenue (as in Germany) they do not have direct 130 Economic Policy Committee (2001): "Budgetary challenges posed by ageing populations" 82 The social dimension of health Section 2 women. Furthermore, Information and Communication Technologies offer improved monitoring of practices against standards. The system remains predominant in Belgium, Germany, France and Luxembourg. access to the money but instead must pool it at national level. Self-funding social insurance plans only exist in Austria. There are three main methods for allocating resources to devolved purchasers: full retrospective reimbursement for all expenditure; reimbursement for all activity based on a fixed schedule of fees; and prospective funding based on expected future expenditure. Many European health systems have been seeking to move from the first to the third, adopting prospective budgets. There are a number of options as to how these could be calculated, including bids from the purchasers, historical precedent, political negotiation and objective measure of need. The first three contain the potential for inequity and do not have sufficient incentives for efficiency, so many Member States are adopting more scientific approaches to budget setting. Risk-adjusted capitation is used in Belgium, Denmark, Finland, France, Germany, Italy, the Netherlands, Portugal, Sweden and the UK, while Spain uses an unadjusted capitation system. Such methods are employed for a number of reasons. The aim of risk adjusted capitation is to ensure that purchasers receive the same level of funding for people with equal need for healthcare regardless of external factors such as area of residence and level of income. The choice of adjuster is important but will often depend largely on the availability of data. Capitation systems are based on the payment of a set sum for each patient for a set period of time regardless of utilisation. It provides good predictability and, in theory, a good incentive to the efficient use of available resources. The risk with this system is twofold. On the one hand, physicians may perform fewer tests and procedures than the patient actually needs, in order to save resources, especially if they are able to retain the surplus. On the other hand, physicians may engage in 'cherry picking' or preferred risk selection. Fairness requires, therefore, some risk adjusting procedures. Most countries require physicians to have a policy of open enrolment up to a maximum list size. If there were no limit to the list size, physicians would have an incentive to take on a large number of patients, but would have little time to spend with each patient. The capitation-based system is increasingly common. It is now predominant in Italy, the Netherlands and the UK. It is combined with FFS in Denmark, Austria, Sweden and Ireland, dependent on the status of the patient. Salary based payment has traditionally been predominant in Portugal, until recently, when a certain amount of capitation was introduced. Salary based payments also provide close to half of General Practitioners' payment in Finland (60%) and Spain (40%), in conjunction with capitation and/or fee-for-service. Salary based payments also involve health centre physicians, as in Greece, and hospital doctors in a majority of Member States. Purely salary based payment systems bear the risk of being inefficient with respect to providing the optimal treatment to the patients: as physicians receive a fixed salary, their incentive to devote personal resources to patients may be limited. An amount of capitation can be introduced, with the aim of correcting the lack of incentives from a pure salary-based system, in terms of revenue and efficiency in the use of resources. In some Member States risk adjusted capitation is combined with other forms of resource allocation, such as historical budgeting, in order to protect plans against full financial risk. Other retrospective adjustments are sometimes made based on actual expenditure incurred. These protect smaller plans or purchasers that only cover a small population from random fluctuations in demand. Payment system. In the primary care sector. The development of social security-based payments of physicians involved three distinct basic methods: feefor-service, capitation and salary, each of which has its own set of implications for cost containment. In the secondary care sector. There are two main groups of hospital payment methods: prospective and retrospective payment arrangements. In general there has been a shift away from the passive retrospective payments, under which the payer bears the risk, to prospective payment systems, under which the provider bears the risk. Fee-for-service, when applied with no restriction, leaves the physician free to perform whatever he/she considers suitable for the patient’s sake, and will be paid according to the list of what he/she performed (for example, corrective interventions, medical analysis and technically supported diagnosis). It is often argued that this freedom leads to an inflated list of performances, with cost-increasing effects. Wherever the fee-for-service system is still predominant, corrections have been progressively introduced, for example through diagnosis-related 'good practice' profiles, or limitations of technology-based performances – for instance in limiting the number of ultrasound sessions for pregnant The use of retrospective payment methods, including per diem or fee-for-service was widespread in the EU. However, they are largely being replaced by activity related payments, which are sensitive to case mix, such as diagnosis related groups (DRGs). Although administratively simple, per diem payments provided incentives to keep patients in hospital longer than necessary, as the first days of care are more expensive when most tests and interventions are carried out. On the other 83 Section 2 The social dimension of health hand, reimbursing hospitals for each item of service may encourage over-use. Many hospital districts in Finland continue to be paid based on locally negotiated prices by the municipalities. In most EU countries with fee-forservice, however, fee schedules are agreed in advance so that prices are set for all providers and all procedures. Graph 60 Share of employment in health and social work sector in total employment (age 15-64) 20 Diagnosis related groups (DRGs) are calculated on the basis of diagnostic categories. Similar procedures are grouped together and prices set for each category. The payment is received for each admission based on the diagnosis and severity of the case. These are used in most EU countries for the purposes of monitoring activity or for adjusting budgets, but rarely for retrospective reimbursement. Portugal was the first country to utilise DRGs for budgeting. In Italy, DRGs are used to fund cross boundary flows of patients The main disadvantage of this model is the incentive to discharge patients early. Since the system is based on admission, there is also an incentive to readmit patients in order to receive higher reimbursement, or to incorrectly classify the diagnosis in order to attract a higher rate of reimbursement. This is referred to as “DRG creep”. 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 B DK D EL E F IRL I L NL A P FIN S 0 UK EU-15 Source: Employment in Europe 2002, p. 32. ge growth rate of 2.4% and a share in overall net employment creation of 18%. By 2001, 9.7% of total EU employment between the ages of 15 and 64 was in the health and social work sector. However, the chart shows that the employment share in these sectors varies widely across the Member States, with the highest share experienced in Sweden (18.7%), the other Scandinavian countries and the Netherlands. The Member State with the lowest share of staff employed in health and social work (4.6%) is Greece. The figures for Spain, Italy and Portugal are only slightly higher.131 Demand for staff is expected to further increase, particularly in the care sector where a number of Member States currently identify staff shortages. Hence, there will be further opportunities to increase employment in health and social services.132 Prospective payment arrangements seek to control costs by setting limits to expenditure in advance. These methods focus on cost control. There are two primary methods, global budgeting and capitation. However capitation is not a common method of paying hospitals in the EU. More EU countries are developing hybrid methods, which combine global budgeting with casemix adjustment. Prospective payments for all or part of the hospital budget are used in Austria, Belgium, Denmark, France, Germany, Greece, Ireland, Luxembourg, Portugal, the Netherlands, and Spain. In principle, global budgeting is the simplest form of hospital expenditure control. Global budgeting delegates the responsibility for managing the budget to hospital administrators who will seek to make efficient use of the money. There are a number of methods for setting hospital budgets including historical precedent, negotiation or on the basis of the previous year’s activity or estimated activity for the year. While historical data is a fairly good predictor of future outcomes, it is not a perfect one and may reinforce existing inequities. The use of diagnosis related groups for setting or adjusting budgets is becoming more widespread in Europe and can be found in Belgium, France, Ireland, Italy, Portugal and Spain. 2.3.8. 20 % 18 Graph 61 Number of physicians and number of nurses per 100,000 inhabitants 2200 2200 2000 2000 NL 1800 1800 Number of nurses 1600 1400 IRL 1200 A 1400 B 1200 DK UK 1000 1600 FIN S D F 800 1000 EU 800 L I 600 600 E 400 P 400 EL 200 0 100 200 300 400 500 600 200 700 Number of physicians Source: Eurostat Health staff Physicians The dynamism in the EU health and social work sector in recent years has been considerable. Net creation of employment from 1995 to 2001 amounted to more than two million jobs, which corresponds to an annual avera- There are 350 physicians per 100,000 inhabitants in the EU, which is significantly more than in the United States (250), Japan (200) and the central and eastern European 131 See "Employment in Europe 2002", p. 28 – 32; data source: Eurostat, LFS. 132 COM(2002) 774 pp13,19. 84 The social dimension of health Section 2 A considerable ageing of physicians has been observed. Between 1995 and 2000, the number of physicians aged 44 and below decreased by 20%, while the number aged over 45 increased by 57% (average for Member States). Ageing of physicians was reduced by an inflow of women, who make up the majority of physicians below the age of 36 but only 16% of the 55-64 age group. One cause of the reduced staff numbers is limited access to medical education, for a number of reasons. If trends continue, France, for example, will experience a 24% decrease in the ratio of physicians to inhabitants throughout the period 2000-2020133. Shortages of physicians are likely to appear in more Member States in the 2010s. Furthermore, these estimates do not take account of the impact that the recent Working Time Directive will have on the availability of doctors. countries (300). However, as can be seen in the graph, there are variations between Member States, within a ratio of one to three. At one end there is the UK with 175 physicians per 100,000 inhabitants (only NHS), and at the other end Italy with 590 physicians per 100,000 of the population. Most Member States vary between 300 and 450 physicians per 100,000 inhabitants. Graph 62 Share of general practitioners and physicians in hospital in the total number of physicians - 2000 80 80 General Practitioners Physicians in hospital 70 70 60 60 50 50 40 40 30 30 20 20 10 10 Nurses. The average number of nurses per 100,000 inhabitants in the fifteen Member States is 950. The figure varies between 2,000 in the Netherlands and 350 in Greece and Portugal. Of all nurses, 56% have tertiary educational qualifications and, in six Member States the proportion is above 85%. A progressive ageing of nurses is reported across the EU; in seven Member States 40% of nurses are already more than 45 years of age and in another five Member States almost one in two nurses have reached this age. 0 0 B DK D EL E F IRL I L NL A P FIN S UK EU15 Note: DK, UK: 1999; B, D, IRL, I, P: 1998; EL: 1997 Source: Eurostat and WHO. The number of physicians in the EU increased over the last decade by an annual average of 2.2%. The rate of change has been highest in Ireland (at over 4.9% per annum), and only three Member States (France, Denmark and Sweden) have experienced a change below 1% per annum. Slow growth is a determinant of shortage; for example Denmark is to bring in 600 physicians from Germany. There are two main factors that provoke the widespread ageing of nurses: 1. 'Stop-and-go' recruiting. For example, in Sweden, recruitment close to zero over the 1990s meant that 59% of nursing staff were above the age of 45 in 2001, leading to very high replacement needs in the near future. As a total of all physicians, the average proportion of general practitioners is 31%, ranging from 11% in Spain to close to half in Belgium, France, Austria and Finland. The share of physicians working mainly in hospital appears roughly to be inversely correlated with the number of general practitioners, with a proportion below one third in France and Italy, and above two thirds in Portugal. 2. The low professionalisation model. High staff turnover requires inflows of young people into the working age population to ensure replacement. Italy is the clearest example here, where demographic decline brings about nursing shortages. The counter-example is Spain, which still shows a surplus of nurses who are highly qualified and regularly increase in number. Although all Member States require a minimum of six years basic medical training, medical specialist training varies in length, usually requiring between three and five years postgraduate training. Since 1995, under the Doctors’ Directive (93/16 of the EEC), a minimum time of two years speciality training has been obligatory for general practitioners in the EU, of which six months need to be spent in a general practice setting. From 2006, a new European recommendation advises a minimum of three years training for General Practitioners. Many Member States now place a requirement on doctors to participate in ongoing medical education. However, re-certification of doctors is not yet compulsory in all Member States. While requirements due to overall population ageing are increasing, the way to prevent demographic decline from causing further shortages of nursing staff is certainly to combine high professionalisation with regular recruitment. Dentists. The number of practising dentists per 100,000 inhabitants lay at an EU average of 62 in 1996, ranging from values of 37 in Spain to over 100 in Denmark and 133 See Drees, Etudes et Résultants, n° 161, March 2002. 85 Section 2 The social dimension of health Graph 63 Distribution of nurses and midwifes* 2001, per educational level A comparative analysis of the vocational education and training of nurses in the EU Member States 0% 20% 40% 60% 80% 100% 20% 40% 60% 80% 100% L EL P A I B D NL E DK UK F IRL FIN S EU15 Nursing is a growing professional sector in Europe. The number of nurses more than doubled between 1980 and 2000 (from 1.2 million in 1980 to 2.6 million by the late 1990s)134. This is a common feature in all EU Member States, with the exception of Sweden, where there was a small decline, and the UK, where the number of nurses was stable135. About 90% of nurses are women and between 82% and 98% of nursing students in the EU/EEA are women136. 0% High Medium Low Monitoring analysis carried out by CEDEFOP* reveals that education of nurses has gone through significant changes since the 1970s in all EU Member States. Although there are still differences between Member States, the general situation is as follows: Note: *Nursing and midwiery professionals (ISCO 223) + associate professionals (ISCO 323) Source: Eurostat - LFS 2001. Graph 64 Distribution of nurses and midwifes* 2001, per age group a) Nurses educated to secondary level are "assistant Nurses" and have limited responsibility. 0% 20% 40% 60% 80% 100% 60% 80% 100% L EL P A I B D NL E DK UK F IRL FIN S EU15 b) A general care nurse or a registered nurse is educated beyond the secondary level, in a professional vocational training college or at University level. Within this sector there has been an organised European system of qualifications since 1977137. c) Post-Basic specialisation is the way most nurses in the EU do their further education and training, after acquiring the general care nurse qualification. 0% In recent years, European convergence has been apparent in the nursing profession. Across the EU, nurses have been upgrading their educational status with a movement towards training and education taking place at higher (university equivalent) level. 40% 20% 15_24 45_54 25_34 55_64 35_44 Note: *Nursing and midwiery professionals (ISCO 223) + associate professionals (ISCO 323) Source: Eurostat - LFS 2001. Graph 65 Distribution of nurses and midwifes* 2001, Growth p.a. 1980-98* * Key points taken from “A comparative analysis of nurse vocational education and training (VET) in the EU Member States” CEDEFOP - 2003 -1 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 L EL P A I B D NL E DK UK F IRL FIN S EU http://libserver.cedefop.eu.int/vetelib/eu/pub/cedefop/internal/2003_0001_en.doc -1 Note: *Except DK: 1995; B, F: 1996; EL, I: 1997; IRL 1990-99; S: 1990-96; UK:1995-98; EU as weighted average of B, DK, D, EL, F, I, FIN, A, S. Source: Eurostat - LFS 2001. 134 135 136 137 ESTAT - Key Data on Health Employment in Europe, 2002 according to the input from the Refer Network Members.. Council Directive 77/452/EEC of 27 June 1977 general nurses; see also Proposal for a Directive of The European Parliament and of the Council on the Recognition of Professional Qualifications Directive 2001/19/EC Section 3, article 29. 86 The social dimension of health Section 2 Greece. Nine tenths of dentists work in private practices, although this proportion is less than two thirds in the Nordic member States and Ireland. red to western European standards. It can be deduced that healthcare still does not have the highest priority. This is particularly the case in Romania where the relative health expenditure is less than a third of the European Union average. However, the graph also shows that Slovenia and Malta have relatively high shares of their GDP spent on health, with Malta even exceeding the average EU relative health spending. Pharmacists. The number of pharmacists per 100,000 inhabitants varies even more. The EU-average is 74 pharmacists per 100,000 inhabitants, with 19 per 100,000 in the Netherlands and over 100 per 100,000 in Belgium, France, Italy and Finland. Again this illustrates a wide diversity in systems of healthcare delivery, payment methods and regulations on the provision to supply pharmaceutical products. Graph 67 healthcare expenditure in the acceding States and candidate countries as % of GDP 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 140 2 2 120 1 1 100 100 0 80 80 60 60 40 40 20 20 0 0 Graph 66 Number of dentists (1996) and pharmacists (2000) 160 160 Dentists Pharmacists 140 120 EU15 B DK D EL E F IRL I L NL A P FIN S EU 1999 0 Source: Institute for Advanced Studies Vienna Data: WHO regional database Europe The measures taken by governments in order to reform their healthcare systems are numerous and reflect the large variety of conditions the systems were in prior to the reforms. Predominant reform efforts have involved making health funding independent of the general state budget and decentralising health to local regions and authorities. Moreover, there has been an amount of privatisation, which has allowed private institutions to run the health insurance systems. In association, private resources devoted to health (out-of-pocket payments and private insurance) have increased considerably138. By the end of the 1990s, however, full public finance of total health expenditure can still be observed in Romania and maybe in Bulgaria (where 1994 data is the latest available). In the Czech Republic and Slovakia the publicly funded share is over 90 percent. Eight of the thirteen acceding States and applicant countries experience a share of public funding at around three-quarters of the current average EU level. UK Note: For pharmacists, 2000 except IRL, I, NL, P: 1999 and B, S: 1998 Source: WHO 2.3.9. RO LV BG TR EE LI 2000 PL SK HU CZ SL MT 1998 2000 1994 1998 2000 1999 2000 2000 2000 2000 2000 Healthcare systems in the acceding States and applicant countries: an overview. Central and eastern European acceding States and applicant countries are building market economies based on the West European pattern. For most of the countries concerned, the transition period began with the collapse of the Soviet Union and the associated breakdown of previously centrally planned markets for goods and services. However, since the mid-1990s, there has been some economic recovery and most of the central and eastern European acceding States and applicant countries have been experiencing, on average, higher real Gross Domestic Product (GDP) growth than the Member States, with only Romania and Bulgaria lagging considerably behind. When the structure of the healthcare system in the acceding States and applicant countries are examined, it is important to make the two following observations. The reform processes taking place in the acceding States and applicant countries have also affected healthcare systems. Despite substantial reorganisations, health services in these countries are still characterised by chronic shortages of funding, with corresponding consequences for health conditions. Health expenditure as a percentage of GDP – shown in the graph – is still low compa- ● On average, there is a relatively strong inclination towards hospitalisation. For example, the number of acute healthcare beds, as a percentage of the population, tends to be higher in most of the acceding States and applicant countries than in the current European Union. 138 Institute for Advanced Studies. Health and healthcare Systems in the Applicant Countries. Vienna, August 2002. 87 Section 2 The social dimension of health Graph 68 Acute care hospital beds per 100,000 inhabitants 800 800 700 700 Graph 69 Number of physicians and number of nurses per 100,000 inhabitants in the acceding States and candidate countries 1000 1000 600 EU CZ 900 900 600 500 500 400 400 300 300 200 200 100 100 0 Number of nurses 800 SK HU CZ LI LV EE SL MT TR EE 600 600 LV 500 400 500 RO 400 300 HU TR 200 100 EU 150 200 250 300 350 400 200 450 Number of physicians Note: Data refer to the year 2000 except BG: 1996 and EU:1999. Note: Data refer to the year 2000 except HU (physicians): 1999; *except EU for nurses: Eurostat LFS2001 Source: Institute for Advanced Studies Vienna Data: WHO regional database Europe Source: Institute for Advanced Studies Vienna Data: WHO regional database Europe Overall, the relative number of in-patient care admissions is higher in acceding States and applicant countries than in the current EU – only Turkey, Poland Bulgaria and Slovenia have smaller figures. The average length of stay in hospital is higher than the EU average in five countries: Czech Republic, Bulgaria, Latvia, Lithuania, and Slovakia. Here again, at the bottom of the scale is Turkey with an average length of stay in hospital that is half the length of the EU average. ● 700 SL 300 0 BG 800 LT SK 700 hours, inadequate rest or disruptive working patterns. Working time limitations in the acceding States and applicant countries might lead to a decrease of services supplied and medical treatments offered due to limited staff capacity unless additional staff are recruited. The resulting staff scarcity might be further intensified when freedom of movement is extended to the current acceding States and applicant countries. In other words, once movement barriers have been removed, medical staff may be attracted by higher salaries available in the current Member States. On the other hand, the number of medical staff is lower in the acceding States and applicant countries when compared to the EU average. This can be seen in the graph below (the graph does not contain Malta, Cyprus and Latvia). All of the acceding States and applicant countries considered have figures below the EU average in both of the medical professions. The relative number of physicians in the acceding States and applicant countries varies within a range of one (Turkey) to three (Lithuania), whilst the number of nurses varies within a range of one (Turkey) to four (Czech Republic). The challenges to the healthcare systems in the acceding States and applicant countries are significant. This is not only due to the forthcoming demographic changes these countries will face, but also because health indicators show that health conditions in most of these countries are still considerably below the EU average, despite recent improvements (see section 2.1). This is true despite the fact that the levels of service available in some countries is not much below, or even better than, the EU average, particularly considering acute healthcare beds. Hence, there is evidence that services are inefficiently used in some cases140. For example, the high number of beds does not necessarily reflect a larger hospital infrastructure. In many cases, higher availability of beds is accompanied by a poor provision of other facilities like diagnostic equipment, drugs or even heating and food.141 The limited supply of heath staff in the acceding States and applicant countries may become a more serious problem when the European Union Working Time Directive of 1993139 is applied. The overall aim of this directive is to protect the health and safety of workers throughout the European Union. Focal points are adverse effects of health and safety caused by working excessively long 139 Directive 93/104/EC of 23 November 1993 140 Health and Healthcare Systems. 141 See WHO: The European Health Report 2002, p. 122. 88 The social dimension of health Section 2 2.4. Society and health ● Social support is important for health and is particularly crucial for good health at both ends of life. Social networks of relatives and friends contribute to protect and enhance the health of individuals, as well as exerting control on deviant behaviour and most lifestyle-related factors. They can facilitate access to health and services, provide a great deal of informal care and help attenuate the impact of negative life events. For people over 55, increasing age brings about a decrease in the size of the social network. People living in poverty are more likely to report higher level of social isolation in most Member States. ● The family remains the bedrock of care and support for both children and adults in all Member States and the role of the family in the provision of care is perceived as important and positive. In total, 6% of all Europeans provide care for sick or disabled adults and the elderly. Overall, 55% of Europeans consider it is a good thing that working adults may have to provide more support to their parents in the future. For the acceding States and candidate countries, the value is 76%, on average. ● All Member States will face a reduction in average household size – the average for 1999 (2.4) was lower than the 1981 average (2.8). The scenarios for EU15 in 2020 show that elderly women will be living alone to a very high extent in the future: extrapolations show that 46% of people over 85 will live alone, 80% of who will be women. This can be considered in conjunction with the fact that the risk of impairment increases with age. Present surveys show that almost 40% of the elderly declare that they suffer severe impairment in daily life activities and a further 30% declare to suffer some impairment. In the future, a large share of elderly people will be living alone and may need external support for their daily activities. ● The future ability of the families to provide care will be affected by developments in the activity rates of women and rates of marriage, divorce and fertility. Within Europe there is a preference (80% of people in Member States and 85% of people in the acceding States and candidate countries) for social services to assist the elderly in their own homes rather than in residential care. ● The organisation of long term care for the elderly shows considerable variations between Member States. There are new initiatives within this field, organising the delivery of professional care either at home or in day care centres or in special long term care institutions. Third sector organisations also try to meet increasing demand for services in social care and welfare by increasing their activities in these sectors. The percentage of people claiming their health to be bad or very bad is significantly higher for the income poor group than for the non-poor (13% and 9% respectively), and higher still for the group of persistent poor (15% for those with income poverty for three years). Furthermore, in all countries, the poor express higher levels of subjective social isolation. Availability of informal support is consistently lower for people in the lowest income group in all countries except for Denmark, France and Italy. ● Universal or near universal rights to healthcare can be found in every Member State, which is a major step for protecting the rights of previously excluded social groups. However, the increase in the proportion of private expenditure, within the total mix of healthcare funding, has now put a greater funding burden directly on the poor and those in poor health. ● The income level influences the utilisation of the healthcare system and the relationship between needs and treatment. Individuals with higher income are more likely to receive specialist services whereas those with lower incomes tend to use general practitioner care. ● Mental health problems are increasingly significant. In the EU, about a quarter of new disability benefits are attributed to mental ill-health. Mental health problems account for a high share of total healthcare costs and consultations with general practitioners. Many of the external causes of deaths, such as homicides, could be linked to mental disorders associated with problematic alcohol and drug abuse. Mental health problems are also related to unemployment and particularly to long-term unemployment of the young. 89 Section 2 The social dimension of health ● Suicides as a fatal outcome vary significantly between countries (much lower reported values of incidence rate in the southern regions as compared to the northern countries), age (peaking between 40 and 55 for men and increasing again for elderly men) and sex (values are much lower for women). ● There are more than 50 million people living with disabilities in Europe. On average, 14.5% of the working age population report being either hampered (10%) or severely hampered (4.5%) in daily life activities. Young people make up of 5% of the people with disabilities, while people of working age represent 46%. Up to half of the people declaring disability are older than 60. ● The rate of employment of people with severe disability is only a third of the rate of employment for people without disability. It reaches two-thirds for people with moderate disability. The age effect is very strong for the three groups and employment rates decrease sharply after 45. ● Disability benefits are the third largest category in terms of social protection expenditure in the European Union, with value ranges from 0.7% of GDP in Ireland to 2.8% in Finland. According to a survey of disabled people in seven Member States, around 93% of the respondents found that the benefits received were inadequate and the largest share of the disabled people find themselves either in a very poor or in a poor situation. Introduction converging social values). There is a hypothesis that people living in more egalitarian societies appear to be less exposed to health deficiencies than people living in a more hierarchical infrastructure. In such a 'peckingorder' society the culture of inequality typically generates more aggressive, violent and discriminating behaviour, which causes stress, humiliation and fear with negative health effects. It has been shown that income inequalities are positively related to violence and crime. This chapter analyses the importance of social networks for ensuring quality of life, the contribution of third sector organisations and the problems of social exclusion in relation to health and care needs. It also presents data on people living with disability or chronic health problems and the forms of barriers to social participation they encounter. As the quality of mental health is particularly affected by social and economic factors, analysis of the prevalence and impact of mental disorders are presented in more detail. 2.4.1. Possible pathways through which social support functions impact health can be identified. 1. Social support can be instrumental: it facilitates or restricts access to medical care, services, and amenities. Social cohesion and health Social cohesion refers to the extent of networks and solidarity among groups in society. High social cohesion implies the presence of strong social bonds, high levels of trust and strong norms of reciprocity. 2. Social networks give emotional support and help attenuate the impact on health of negative life events (e.g., loss of a job, divorce or death of a relative) and help adapt to long term difficulties. They provide effective support, increase self-esteem and contribute to limiting stress and feelings of insecurity. Social Cohesion is a key health determinant… Social networks work both directly and indirectly to protect and enhance the health of individuals. This link between social relations and health has been discussed for over 100 years: "More socially isolated people are more likely to commit suicide" observed Durkheim in his pioneering work of 1895, when comparing the difference in suicide statistics in European countries across time. Social networks are the aggregate expression of individual relationships, which build on the totality of the social resources to underpin and address different life problems. Social networks aggregated at community level reflect the availability of social links, reciprocity and institutionalised conflict management. It creates a degree of social cohesion (absence of social conflict and 3. Social context also affects personal behaviour and lifestyle-related factors, through the risk tolerance in the person’s network: this has been observed particularly for alcohol, tobacco and drug abuse, but also for quality of diet and the amount of physical exercises. The networks control the diffusion of healthrelated information and exert social control over deviant behaviour. 4. The cognitive aspects related to the social context, such as social trust and shared values, also increase feelings of security and self-esteem within and between communities. Social support also bolsters selfefficacy and vice versa, increasing empowerment. 90 The social dimension of health Section 2 ... particularly through social networking … this age group is still rather low. For some specific causes of death, the relative risk is even much higher. For men who lost their spouse, the suicide rate and death from alcohol-related diseases are three times higher than for married men, deaths from chronic ischaemic heart disease and from other circulatory diseases are two times higher, and even lung cancer, stomach cancer and motor vehicle accidents are 50% higher. Social networks are an amalgamation of resources a person can rely on when dealing with different life problems and stress, such as personal losses, physical or emotional disabilities, diseases and working stress. It seems that social support affects the response to stress and the level of reactivity. The impact increases with age, as recovery after a stressful event is more prolonged for older people. Social isolation also influences the regulation of immune mechanisms and immune responses to infections142. The form and amount of support depend on a person's skills and abilities to mobilise social support: education (including lifelong learning) and employment status are important determinants, as are living arrangements (living with a partner, with children, etc). Social isolation is reported as the second strongest factor (after financial difficulties) affecting psychological distress143. A Swedish study tracked mortality and morbidity for 400,000 mothers between 1992 and 1994 and the results testify the vulnerability of single mothers, even in Sweden144. Their mortality risk is 1.53 compared to 1 for couple mothers. Particularly high risks are found for lung cancer (2.31145), suicide and suicide attempt (2.53), psychiatric disease (2.49), addiction (4.17) and violence (6.38). The extent and patterns of social networks are quite difficult to measure, however European Community Household Panel (ECHP) data does contain some useful information on the level of contact with friends or families in a given period. Social relations in the southern Member States and Ireland tend to be more informal, based on neighbourhood and community interactions, whereas in the north, there is more participation in formal clubs and associations. Considering informal relations, on average four out of every five Europeans talk to a neighbour at least once a week. This is especially true in Greece, Spain, Ireland and Portugal. The Netherlands, Denmark and Luxembourg display the highest levels of people having such contact with friends less than once a month or never. Mortality and marriage. One of the most important studies on excess mortality after the death of a spouse was carried out over the years 1986-1991 for 1.58 million married Finnish men and women aged 35-84 (Martikainen and Valkonen 1996). On average, men have a 21% higher risk of dying after the death of their spouse than married men of the same age. Women have a 9% higher mortality risk after the death of their husband. The family network is one of the earliest and most important determinants of health. Furthermore, relatives, friends or peers usually provide informal social support, while social services, churches, groups, or other specific institutions provide more formal assistance. Graph 70 Excess mortality after the death of spouse (Finland 1986-1991) 1,7 1,7 Widowed men Widowed women Non widowed persons 1,6 1,5 1,6 1,5 1,4 1,4 1,3 1,3 1,2 1,2 1,1 1,1 1,0 1,0 0,9 0,9 0,8 It is important to note that social support should not be considered as static. Social networking is a dynamic phenomenon. It is influenced by the stage the person is in the life cycle. It is particularly affected by the changes in social roles of the person. Support exchanges are to be considered in a lifetime context as they are based on ties and shared history. This is particularly crucial at both ends of life: 0,8 Total Age 35 - 64 Age 65 - 74 Age 75 - 84 Source: Martikainen and Valkonen 1996 ● The increased health risks due to the death of one’s spouse are by far the highest below the age of 65: 66% for men and 25% for women. Here the relative difference is visible because the mortality of the married population in The importance of relationships with parents or other carers during childhood is well documented. Affectionate, attentive and stable caring allows infants and children to develop functions such as language, intellect and emotional regulation in a normal way. Children deprived of such nurture are more like- 142 L.Berckman and I Kawachi (ed.), Social epidemiology, 2000. 143 Social precarity and social integration – Report for the European Commission based on EB 56.1 - D.Gallie and S. Paugam 2002 144 In: Income and health: a review of the literature and an empirical analysis, by the Social and Cultural Planning Office, NL, for the European Commission, 2002. 145 OR Odd ratio- cited in INCOME AND HEALTH. Review of the literature and empirical analysis – CPB (ref). 91 Section 2 The social dimension of health ly to develop mental and behavioural disorders, either during childhood or later in adult life. ● ● Graph 71 Percentage of population declaring their health as good or very good 90 In the case of ill health or disability, the number of informal contacts with friends and neighbours tends to decrease. Social isolation is higher for people with severe disability. 90 % Active Inactive 80 For people over 55, increasing age brings about a decrease of both network size and the amount of informal support. The average female network size is usually slightly larger than that of men at all ages over 55. Another difference is that women are more likely to have a high proportion of family and friends in their networks, whereas male networks are more work-oriented. 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 15-24 25-34 35-44 45-54 55-64 65-74 75-84 Source: ECHP 1999 access to important prevention programmes for health, which are developed in the workplace in accordance with health and safety legislation. For people not in employment these services are not available. In other words, people not in employment face specific and significantly stronger health problems, but have reduced access to regular health screenings. Some countries have proposed free annual health screenings and access to health education to counteract this. Social networks can also be evaluated, through indicators of participation in social institutions and marriage and the expression of a sense of support ("I have someone to rely upon"). It is well known that being in a stable partnership and having responsibilities for child rearing contribute to protect against mental health problems. … by fostering opportunities for social participation… …and increasing social capital … Social participation and social engagement (in workplaces, churches, sport clubs and civil organisations) contribute to provide a sense of value, belonging and attachment. Through these repeated contacts and participation life acquires a sense of coherence, meaningfulness and interdependence. It is particularly important to devote resources to the development of social networks at all stages of life. For older people, social participation is related to the maintenance of cognitive capacity and reduction of mortality146. Particular attention should be given to activities supporting social participation and networking for retired people. Social capital, in terms of levels of trust or participation in social networks, tends to impact on several determinants of social quality, including the level of criminal activities, educational outcomes, youth development, work involvement and economic development. Sharing norms and involvement in networks – formally or informally – facilitates collective action and increases the chance to engage in economic exchanges. American research surveys show that social capital also impacts on health. Levels of membership in various organisations (for example churches, sport and trade unions) in the US was strongly inversely correlated with age adjusted mortality rates. Level of involvement in civic associations is a predictor of death by cardiovascular disease or cancer and infant mortality147. Other studies show that, independently of individual risk factors, the community (or regional) social capital has an impact on individual well being and self rated health, with correlation between income inequality, (lack of) social trust and mortality. Participation in employment is the main form of social participation in our society. The employment rate for men reaches 73% in the EU and 54.9% for women. For people over 54, the values are respectively 48.7% and 28.9%. Section 3 gives data on the employment rates for all Member States, with a specific attention to the groups of young and older workers. Analysis from the European Community Household Panel show that inactive people consult doctors more often than active people (which is discussed in more detail in section 2.2 of this report). Active people are more likely to declare their health as good or very good. This holds true for all the age groups up to 75. The largest difference is recorded for people in the age span 45 to 54. However, it is difficult to replicate these findings with European data. For example, distrust showed no (significant) relationship with age-specific mortality or life expectancy. In most surveys, interpersonal trust is recorded as high in Scandinavia and low in France, Belgium and southern Europe, whereas the highest values for Participation in employment gives access to a wide range of resources. It provides better income but also 146 L.Berckman and I Kawachi (ed.), Social epidemiology, 2000. 147 Kawachi et al (1997,1999), in L.Berckman and I Kawachi (ed.), Social epidemiology, 2000. 92 The social dimension of health Section 2 female life expectancy are found in Italy, France and Spain and not the Scandinavian countries. Countries with greater trade union membership and political representation of women have better child mortality profiles148. In the EU, social capital is best measured in terms of density of networks, relationships and active participation, and furthermore, social dialogue plays a critical supporting role149. In the acceding States of central and eastern Europe, previous healthcare systems were heavily centralised. There was a lack of associations and of an autonomous civil society. This was the sign of a more passive attitude on issues that the state was assumed to take complete care of. People were more passive on the issue of health prevention and thus felt little personal responsibility for their own health. …which strengthens the potential for health promotion strategies. 2.4.2. Across Europe, local-community initiatives are used to offer integrated assistance in tackling health inequality problems. Such approaches allow the broad determinants of health to be addressed at the level of a territory or community. In particular, community services, developed with the involvement of residents and local associations, can provide innovative solutions. Special needs of specific groups (such as immigrants or ethnic minorities) can also be better tackled in this way. Social exclusion and health This chapter considers how the care needs for people at high risk of social exclusion are covered in terms of informal support, access to the healthcare system and recent policy developments. Poverty affects health determinants… Living in poverty contributes to lower the quality of life and the health status. At the EU level, the percentage of people claiming their health to be bad or very bad is significantly higher for the income poor group than for the non-poor (13% and 9% respectively – ECHP, 1996). It is even higher for the group of persistent poor (15% for those with income poverty for three years). In each age group, people with poor financial resources also claim more frequently that they have obstacles in their daily activities due to chronic health problems, than the more wealthy groups. The effect is particularly strong for people living in poverty for a long term such as four or five years. This two-way link between income and health is presented in more details in Chapter 2.2 of this report. Health promotion is a major area of focus in terms of public health. It aims to enable people to utilise the control they have over their health determinants. It encompasses actions aimed at lifelong health education and awareness and others directed at changing social, economic and environmental conditions 150 On several topics, such as nutrition, consumption of alcohol, tobacco and drugs, physical exercise, mental health, sexual behaviour and use of medicines, health promotion programmes tend to improve knowledge about risk factors and encourage people to adopt healthy lifestyles and behaviour. A detailed study in Portugal on "health and healthcare of the disadvantaged people" found that nearly all respondents reported their health status as "less than good". Despite these unfavourable health conditions they have lower utilisation rate of healthcare services than the population in general and routine medical appointments are less frequent. Programmes for health promotion can be effectively supported by local associations who possess the capacity to be nearer to the local situation and needs. Community development has more chance to be successful in communities where social capital, levels of trust and co-operation are high. This strengthens the probability of success of intervention programmes for health promotion, including programmes of education, prevention of violence and drug abuse. There is now more and more research organised to understand how social capital contributes to health promotion programmes and vice versa151. Studies in northern Member States show that the same categories of people are more likely to be in poverty (albeit at a much lower level): single mothers and their children, elderly living on small pensions, long term unemployed, immigrants and the marginalised, such as hard drug users and the homeless. For example in Sweden, health status is reported as "less than good" by 36.5% of single mothers who are living in poverty and by 26.8% of the non-poor single mothers. The values for those living in a couple were 19.5% for the poor mothers and 17.1% for the non poor, which again shows the protective effect of marriage. Non-Government organisations (NGOs) in the field of health appear to be involved in these activities in many countries, particularly in education, prevention, public awareness, patient management and policy development152. 148 Income and health: a review of the literature and an empirical analysis, by the Social and Cultural Planning Office, NL, for the European Commission, 2002. 149 For an analysis of the problems of definition and measurement of social capital, and its links to economic and social policies : Cost of non social policy by D.Fouarge, Report to the European Commission, 2003. 150 See the European Programme of Action in the field of Public Health (2003-2008). 151 Evaluation in Health Promotion: principles and perspectives, WHO, European Series 92, 2001. 152 European health report, WHO - 2002. 93 Section 2 The social dimension of health A Finnish study (Martikainen et al. 2001) analysed mortality rates in relation to income for three million people, aged 30 or over during the period 1990-1996. An almost linear relationship between mortality and income was found, where disposable income corrected for household size is subdivided in deciles. Above the age of 65 years, the association between income and mortality weakens rapidly. Graph 73 Access to potential support in situations of difficulty, by Member State and income group, 2001 80 80 Whole population Lowest quartile Income group 60 60 40 40 20 20 Graph 72 Mortality rate by income level (Finland) Relative mortality rate 2.4 2.4 2.2 2.2 2,0 2,0 0 B DK D-W D-E F UK UK IRL N-I NL FIN S A L I E EL P 0 Source: Eurobarometer 56.1. October 2002 1.8 1.8 Men 1.6 1.6 1.4 1.4 Women 1.2 for those with low incomes, while the inverse is true for the northern countries. 1.2 Availability of informal support is consistently lower for the people in the lowest income group in all countries except for Denmark, France and Italy. While for the population as a whole the proportion of people with someone to count on increased between 1996 and 2001, the "potential support" has diminished for the people in the lowest income group for all the countries, except for the same three countries. 1,0 1,0 1 2 3 4 5 6 7 8 9 10 Income decile Source: Martikainen et al. 2001 Infant mortality is the health indicator most strongly related to poverty This indicator is also particularly sensitive to healthcare spending: studies find that each additional 1% in per capita healthcare spending is associated with a reduction of 0.184% of the infant mortality rate. There are persistent differences in infant mortality levels among social groups and territories. The most important public health policy actions for fighting social exclusion are related to childcare: ensuring correct childcare in the home, providing regular and free access to health screening (including vaccination) and providing preventive care and health education in schools. In the acceding States and candidate countries, social isolation is particularly influenced by education: it is as high as 25% for people who left school at the age of 15 and 11% of the highly educated group. Interestingly, people living in rural communities are more likely (23%) to have functional social support networks compared to the residents of large cities (15%). Graph 74 Access to potential support in situations of difficulty, in candidate countries If I were feeling depressed, there is someone* ... Facing one problem (depression, job search, financial issues, there is nobody** ... Income poverty is not the only issue. Social exclusion points to multiple forms of deprivation faced by people living on a low income. It impacts on the type of support people can find in their social networks. It also influences the level of access and utilisation of public infrastructures, particularly in the domain of health and longterm care. These two dimensions are analysed in more detail in the following paragraphs. 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 ...through multiple forms of social exclusion. SK MT HU PO CZ SLO EST TU CY RO LV BG LT 0 Note: * ... I can rely on to help me from outside my own household ** ...outside the household I can rely upon Social support points to the availability of people that can be relied upon in situations of personal difficulty. In all countries, the poor express higher levels of subjective social isolation: people in the lowest income group are more likely to feel that others do not value them. The unemployed do not have less social contacts, but they nevertheless feel significantly more isolated. Social isolation is also stronger in cities and large towns. In the southern countries (except Portugal), sociability measured by the number of social contacts seems to be higher Source: Eurobarometer CC. Universal coverage… Universal or near universal rights to healthcare can be found in every Member State. This has been a major achievement within the EU in recent decades. The introduction of universal coverage in France in January 2000 is 94 The social dimension of health Section 2 with social exclusion, adjusting to new cultures and marginalisation. perhaps the most significant recent attempt to increase access to healthcare in the EU. France now joins Denmark, Finland, Greece, Ireland, Italy, Luxembourg, Portugal, Sweden and the UK in providing universal statutory health coverage (OECD 2001), significantly reducing the risk of social exclusion from health services. Migrant and refugee groups may experience specific linguistic and cultural barriers to communication, making it difficult to receive accurate diagnoses, particularly with regards to mental illnesses. Inadequate knowledge among medical practitioners and social workers about the specific needs of migrants act as further barriers to treatment. Few countries have developed comprehensive health policies concerning migrants and refugees. Specific actions are needed to train social and health services staff, to provide interpretations and to design adequate health promotion strategies. Community initiatives, involving peer educators, lifelong learning facilitators, cultural mediators and community interpreters, are important for educating and empowering migrant groups. Chapter 2.3 presented data on coverage analysis but also on the significant increases in the proportion of private funding for healthcare during the 1980s and 1990s. In depth analysis suggests that the achievement of universal rights to healthcare, in terms of universal coverage, has been accompanied by a process of selective ‘de-insurance’. That is to say, at the same time as statutory health insurance has been extended to cover the whole population, the comprehensiveness of this cover has declined on the whole. Again, considering the French example and the implementation of the CMU in January 2002, five million people are now covered without cost by the universal health coverage scheme (CMU). However, the extent of the package of services to which these beneficiaries are entitled to, at no cost, is still under discussion. The introduction of universal coverage legislation provides a framework for protecting the needs of previously excluded social groups, but does not in itself guarantee change. In spite of the official achievement of universal or near universal statutory health insurance coverage, there are persistent problems of access. During the 1990s several Member States introduced policy initiatives to improve effective access. Some initiatives were aimed at reducing waiting lists, with mixed results. Several Member States enshrined the rights of patients in law (Finland, Greece, Denmark and the Netherlands) or used patients' charters as a tool to promote patients' rights (France, Ireland, Portugal and the UK). Access can also be facilitated through general policy aimed at a geographical balanced distribution of health services, and to local initiatives, fostering better co-ordination between social and health services. …does not guarantee universal access… Access to healthcare has been defined as “the actual use of personal health services and everything that facilitates or impedes that use”. From an economic perspective, barriers to access can be associated with supply-side factors, such as service availability and distribution, the location of health services and the existence of waiting times for treatment. On the demand side, barriers may be financial (cost of services or opportunity cost of using care), psychosocial or sociocultural. Furthermore, knowledge, information, beliefs and preferences influence the use of health services. Many Member States attempted to remove financial barriers through the expansion of statutory health insurance coverage. At the same time, the increase in the proportion of private expenditure in the total mix of funding for healthcare put a greater funding burden directly on poor people and people in poor health. When basic co-payment is seen as necessary, some Member States implement policies to limit individual or household health expenditure to a certain ceiling, for example an annual maximum health bill. In addition, some Member States offer services at a lower cost to low income groups through means-tested contributions exemptions. The special needs of migrants Migrants represent a diverse group of people and it is difficult to generalise about their health needs. Nonetheless, migrants, their second and third generation descendants, illegal immigrants and refugees often have particular health concerns and face difficulties in accessing health services. Migrant groups and refugees often experience specific health concerns, which can stem from problems encountered in their country of origin, or which are exacerbated by poverty and social deprivation experienced in their new country. For example, many refugees experience poor nutrition, poor quality housing or inadequate sanitation and poor quality neighbourhoods. Many are insufficiently vaccinated against common communicable diseases. This can lead to an increased risk of developing respiratory disorders and diseases such as hepatitis B and C or tuberculosis. Work-related health risks, including occupational accidents and the impacts of labour market discrimination, are another concern, together with mental health problems linked In almost all Member States, treatments in dental care and pharmaceuticals are fully or partially excluded from coverage and patients must make out-of-pocket payments or purchase complementary voluntary health insurance to cover the cost of these, decreasing the affordability of some treatments. According to a Eurobarometer survey 52.1, the proportion of people consulting a dentist in the last 12 months varies widely among Member States. Education and 95 Section 2 The social dimension of health income levels appear to impact on the use of dentists: consulting a dentist is 50% more likely for the people with the highest education level as compared to the people with the lowest. The income effect is very similar: 48% of the people in the lowest income said they had consulted a dentist compared to 69% of the people in the highest income group. Graph 76 Over-utilisation of medical resources -50 0 50 L UK GP visits E Specialists visits I 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 NL D EL P -50 E P IRL EL I FIN A B F UK D S L NL 0 50 100 150 Note: *Ratio of the number of visit to physicians by individuals in the top income group as compared to people in the lowest quintile (after standardisation by age, sex, health status). Source: Eurostat (based on ECHP data 1996). resources. This differential use pattern results in a variation in the quality of treatment received; people in equal need cannot be said to receive equal treatment at all income levels 0 0 Total physicians B Graph 75 Proportion of respondants who consulted a dentist in the last 12 months 90 150 IRL DK 90 100 EU-12 DK …as addressed in the European Strategy against poverty and social exclusion. Source: Eurobarometer 52.1, 1999. Within the European strategy against social exclusion, all Member States covered the question of achieving better health status and better access for care. In order to provide universal access to healthcare within all Member States a multi-pronged approach is needed for health prevention and promotion and better access to healthcare as described in the Joint Report on Social Inclusion154: …or equity in the use of healthcare systems. healthcare service utilisation is also different for different income groups. Analysis of ECHP153 data on the use of medical services shows that higher income individuals are more likely to receive specialist services whereas lower income individuals are more prone to use general practitioner (GP) care. ● Developing health prevention and promotion strategies. Health promotion and prevention strategies are considered as a priority to tackle the socio-economic health determinants (as discussed in chapter 2.2 of this report). Although these strategies are not specifically designed for the most vulnerable groups they nevertheless play a key redistribution role to the extent that they help reduce financial obstacles and overcome cultural barriers. ● Ensuring affordability and access to healthcare provision by lowering financial barriers and encouraging local or regional initiatives. The Joint Report on Social Inclusion also pointed to the need to adapt emergency services to better respond to emergency cases. This requires responsive emergency services in hospitals and co-ordination between the relevant professionals. ● Launching initiatives to address groups with specific disadvantages. Some groups of people need specific support, such as people with disability or mental health problems, or people with high-risk behaviour The graph shows the relative difference in the utilisation of general practitioners and medical specialists for people in the top and bottom income groups. This analysis is performed using the total number of visits to a GP or a specialist for each income group, corrected to incorporate the effect of sex, age and of self-declared health status. The ratio presented in the graph is therefore directly related to the level of income (and indirectly to the level of education). The graph shows that people in the top income group tend to visit a GP slightly less but utilise specialists (+42%) much more. Lower income groups tend to use more General Practitioner care, but their over-utilisation is less significant when the data are adjusted for needs (according to age, morbidity and sex). The overutilisation of the services for specialist care by higher income users, however, is more obvious. These differences in general practitioner and specialist visits may be due less to the cost determinants than to the higher education levels of the higher income individuals, and their subsequent preference for specialist healthcare 153 Economic determinants of the distribution of health and healthcare in Europe – Ecuity II – E.van Doorslaer – funded by the European Commission – BMH4-CT98-3352). 154 Joint Report on Social Inclusion, European Commission, 2002. 96 The social dimension of health Section 2 patterns, such as users of prostitutes, alcohol or drugs. Mental health problems need to be tackled through various sets of policy measures: greater local co-operation, better provision of outreach and emergency accommodation services and specific training for health and social services employees. 2.4.3. Of the ten most prevalent disabilities, five are mental disorders: unipolar major depression, alcohol dependence, bipolar depression, schizophrenia and obsessive–compulsive disorder. Viewing the increasing prevalence in another way, across the EU, the number of psychiatrists is rising at a rate of 3% per year on average. The causes and impact of mental health disorders vary with different social and economic factors, and also with the level of stress and helplessness. Depression, suicide, alcoholism, and violent and risk-taking behaviour have an obvious impact on morbidity and premature mortality. The onset of mental problems are often linked to a succession of life events, desirable or undesirable, which act as catalysts, such as changes in marital status or in job situation. Mental Health Social activities are particularly affected by mental health. Good mental health is a state of successful performance of mental function, resulting in productive activities, fulfilling relationships with other people, and the ability to adapt to change and to cope with adversity specific to the individual’s culture (ILO, 2000). Mental disorders are health conditions characterised by alterations in thinking, mood or behaviour and associated with distress, anxiety, social dysfunction and depressive moods155. It is possible to examine the relative prevalence of mental health. Several studies have shown that common mental disorders are about twice as frequent in the lowest income groups compared to the highest. A majority of Member States agreed on the importance of mental health issues for people in poverty and social exclusion. Men and women seem to be affected to the same extent by mental disorders but by different types of illness. Anxiety and depressive disorders are more common among women, while substance use disorders and antisocial personality disorders are more common among men. Married men and women seem to have less mental problems than single people: "Married women with children and a job had the fewest mental health problems of the female sample", reported an Australian survey158. As analysed in chapter 2.2, mental health is a key determinant of overall health. Anxious and depressive moods, for example, initiate a cascade of adverse changes in endocrine and immune functioning and create increased susceptibility to a range of physical illnesses. The health behaviour is very much dependent on a person's mental health. Mental health problems are increasing significantly, even when the ageing effect is taken into consideration156. The magnitude of the burden of mental distress and disorders, ranging from stress through depression and neurosis to major psychosis, is generally underestimated. The direct consequences of mental illness can account for between a third and a half of total healthcare costs. Furthermore, it was estimated that 23% of all health service costs in the Netherlands and 22% of inpatient expenditure in the UK were related to mental health. A recent analysis in France, based on 1998 data157, concluded that mental health problems are responsible for 15.5% of total hospital costs and are the second largest part of total healthcare expenses (9.4%), after cardiovascular problems (10.7%). The health impact of unemployment was analysed in section 2.2 of this report. It seems to be higher for men than for women, and also for younger workers than for older ones. Social norms seem to play an important role: the psychological cost of unemployment appears to be less important in areas with high unemployment rates, than in low unemployment areas. Young people who are long-term unemployed have a distinctly higher risk of health-related problems compared to their employed peers. This is especially true for mental health and psychological problems. Studies show a number of psychosocial strains result directly from unemployment, such as feelings of low self-esteem and self-confidence, dependency, fear of the future and apathy. The risks of depression and suicidal behaviour are also related to long-term youth unemployment. Furthermore, unemployment is reflected in young people's health behaviours, such as alcohol and tobacco consumption, abuse of drugs and medicine, and lack of physical activity. The World Health Organisation (WHO) estimates that at least 5% of the population in Europe suffer from serious diagnosable mental health disorders (neuroses, functional psychoses and mental retardation). It is further estimated that wider mental health problems affect between 15% and 20% of all European adults. Mental and neurological disorders figure among the leading causes of disease and disability. In fact, after cardiovascular disease, depression could become the second most important determinant of the global burden of disease by the year 2020 – it is currently fourth. 155 156 157 158 Section 2.1 presents more data on neurodegenerative diseases related to old age. Global Burden of Disease - WHO- 2000. V.Paris et al, DREES, Etudes et resultats N° 188, September 2002. De Vaus D. in New Scientist, October 2 2002. 97 Section 2 The social dimension of health However, research conducted in six European countries (Belgium, Germany, Sweden, Spain, Italy and Greece) suggests that the health-related effects resulting from unemployment are not constant between countries159. Certain cultural and social differences between north and south European countries exacerbate the stress of unemployment, while others protect against it. In all countries, social support is an important resource for the young people affected. The negative health effects from unemployment are less prominent in southern European countries, where social support networks from the family and irregular work help to reduce social exclusion and associated health risks. Graph 77 Suicide and intentional self-harm per sex, 1999 40 30 40 Male Female 35 36,4 35 29,8 30 27,3 25,9 25 22,9 20 25 24,2 22,8 18,6 20 18,7 17,1 15 15 10 12,4 11,8 10,5 9,3 8,3 10 9,2 8,6 8,1 7 5,9 5,9 5,7 5 11,3 10,8 8,7 5,2 4,5 3,2 2,9 3,1 2,1 0,9 B Mental health problems are an important risk factor for health... 5 0 0 DK D EL E F IRL I L NL A P FIN S UK EU 15 Note: B: 1995; DK: 1996; EL: 1997; E, F, IRL, I, S, UK, EU: 1998. Source: Eurostat Mental health problems are linked with physical comorbidity (diseases or disability), risky behaviour and higher risk of substance abuse. Depression has considerable disabling effects and also leads to increased mortality. In Europe, about 25% of new disability benefits are due to mental conditions and this share is increasing. In Austria, emotional (psychological) disabilities were the most frequent reasons for the entitlement to disability pensions, representing 31% of new cases in 2000. In the Netherlands, in 2001 about 35% of the total number of disability benefit recipients were unfit to work due to mental disorders (EIROnline NL). A study using American data (1993) found that nervous and emotional problems (including alcohol and drug problems) and mental illness are the groups with the highest severity in work-disabilities. Compared with other conditions, workers with mental disorders are more likely to go to work but perform below the optimal. This was observed when adequate treatment for migraine, anxiety and depression resulted in the greatest long-term percentage improvement in productivity and reduced work loss days160. Graph 78 Suicide and intentional self-harm per sex and age, 1999 1,8 1,8 1,7 1,6 Male Female 1,6 1,6 1,6 1,5 1,4 1,4 1,4 1,4 1,2 1,2 1,1 1,2 1,1 1 1,0 0,8 0,6 0,5 0,5 0,4 0,4 0,4 0,3 0,2 0,2 0,1 00 00 0_4 5_9 0,2 0,5 0,5 0,5 0,4 1,0 0,8 0,7 0,6 0,0 0,9 0,9 0,4 0,6 0,4 0,3 0,2 0,1 0,1 0 0,2 0,0 10_14 15_19 20_24 25_29 30_34 35_39 40_44 45_49 50_54 55_59 60_64 65_69 70_74 75_79 80_84 85+ Source: Eurostat are relatively low in the southern regions161. Furthermore, the rate is much lower for women than for men in all countries in Europe. The suicide rates are also very dependent on age, peaking between 40 and 55 for men and a little later for women. It increases again for elderly men. Many of the external causes of deaths, such as accidents, poisoning and homicides (see Section 2.1 for a more detailed discussion), could be linked to mental disorders associated with problematic alcohol and drug abuse. Section 2.3 presented data about the use of drugs and alcohol, and drug related deaths, mainly from violence, accidents, overdose and suicides. Considering the number of years of life lost, the impact of suicide at a young age is important: for young men it is the second most common cause of death, after traffic accidents. Being in a stable marital relationship seems to be a protective factor against suicide, for both men and women. The responsibility for bringing up children also provides an additional protection. Suicide rates are higher for single and never married people (at least in Western culture) and the highest rates are to be found among people who are widowed or divorced, particularly men in the first months after such a separation. ... and can lead to fatal outcomes such as suicide... Mental health problems can have fatal outcomes as a large share of depressive patients end their lives by committing suicide. Epidemiological findings point to a significant and unexplained international variation in both suicidal behaviour and suicide rates: suicide rates 159 T. Keiselbach, 2000, Long term unemployment among young people in Europe: A qualitative comparative study on the risk of social exclusion 160 Illness, disability and social inclusion, S. Grammenos, CESEP, for the European Foundation for the Improvement of living and working conditions. 2002 161 Although there may be some underreporting, due to cultural reasons. 98 The social dimension of health Section 2 2.4.4. Dealing with mental health disorders The vast majority of minor mental disorders are addressed within the community itself or at the primary care level: studies show that mental health problems account for up to 30% of general practitioner consultations in Europe. Who provides help? On average, 6% of Europeans162 provide care for sick or disabled adults and the elderly. Relatively speaking, it is the 50-59 age group (11% of them) which takes the major responsibility for this caring, and women (8%) twice as much than men (4%). Traditionally, in many Member States there was a tendency to institutionalise people with mental disorders, which was a severe form of social exclusion. The analysis detailed in Section 2.3 showed that there are large variations between Member States for the number of days spent in hospitals for mental and behavioural disorders. Although trends are reversing – countries in the west of Europe tend to prefer treatment in the community – mental and behavioural disorders still account for one tenth of the total number of in-patient days, on EU-average. This shows that, although being cared for within the community is preferable, it is not yet common practice. Stigma still exists and there is a reluctance of communities to accept people with mental disorders, leaving many patients to the custodial services. Furthermore, data on hospital treatment shows very different levels in the acceptance and ability of society to handle people with mental and behavioural disorders within the community and to avoid their social exclusion. It is largely family members who provide help to those with impairments. This was seen in a recent survey in France163, which showed that 40% of the adults with disability who live at home receive some form of help. The largest group (62%) receive informal help only, a smaller number (13%) receive only professional help, with the remainder receiving a combination of both. In total, 90% of this informal help comes from the family: the spouse (36%), a parent or grandparent (23%), or a child (21%). Neighbours account for 7% of the help providers. The type of informal help provided includes domestic and shopping support, personal care, support for health problems, help with administrative issues and also companionship. The reduction in household sizes is a common trend in all Member States. Each Member State has experienced a decline in household sizes in recent decades. The average household size fell from 2.8 people in 1981 to 2.4 in 1999. The highest values remained in Portugal, Spain and Ireland, with averages between 2.9 and 3 people per household in 1999. Also in 1999, an estimated 12% of the population was living alone. The proportion was highest in the Nordic countries (more than 15%) and lowest in Spain and Portugal (5%). There are marked differences between sexes and across age groups. More than one third of one-person households are made up of women aged 65 and over164. A recent Eurobarometer showed that there is still some reluctance to the community approach to dealing with mental problems in some Member States. In other words, it appears that some countries have a stronger social support in favour of the social inclusion of mentally disabled people than others. Graph 79 Mentally disabled people should be separated from the community ... 30 30 ... Somewhat agree ... Strongly agree 25 25 20 20 18,1 15 15 15 13,1 17,9 12,3 10 The scenarios for EU15 in 2020 show that 20% of people of the 65 to 69 age group will be living alone, with a value even higher (46%) for people over 85. Women will make up almost 80% of this latter group. 15,5 15,3 12,5 10 11,5 When considering these trends in living arrangements for elderly people, it is noteworthy that problems related to disability increase with age (see section below). Present surveys show that almost 40% of the elderly declare to suffer severe impairment in daily life activities, with a further 30% stating that they suffer some impairment. In the future, a large share of elderly people will live alone and may need external support in their daily activities. 6,1 6,8 5,5 5 7,2 4,6 2 0 B 7,8 3,1 4,6 5,5 DK D 3,4 3,9 7,7 5,1 5 8,6 5,7 3,6 4 3,4 4 5,4 3,2 1,2 GR E F IRL I L NL A 0 P Providing care: Importance of informal care and of third-sector organisations. FIN S UK EU 15 Source: Eurobarometer 54.2, 2000. 162 (ECHP data,1995: update). 163 Handicaps-incapacités-dépendance, INSEE HID 1999. 164 More analysis can be found in the DG Employment and Social Affairs report on the Social Situation in the European Union 2001. 99 Section 2 The social dimension of health Graph 80 Share of people living in one person household (in % of the population of the age group) 50 Graph 82 In the future, working adults will have to take care of their elderly parents more than they do nowadays: that is ... 50 Women Men 45 40 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 0 0 65_69 ... rather a bad thing ... neither good or bad ... rather a good thing 45 70_74 75_79 80_84 85_89 90+ 100% 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% 0% LT Source: ESTAT baseline scenario for 2020 (15 countries) The family remains the bedrock of care and support for both children and adults in all Member States. The role of the family in the provision of care is perceived as important and positive. More than half the Europeans consider it a good thing that, in the future, working adults will have to look after their parents more. The lowest support for this shift to family responsibility is to be found in Finland, Sweden, Netherlands and Belgium, with the highest in southern Member States, particularly Greece. This is seen in the graph below. As presented in chapter 2.3, long term care for the elderly is still particularly supported by the extended family in the Mediterranean Member States. In Italy and Spain, the number of long term nursing care beds is less than a tenth of the EU average. Quite a bad thing Quite a good thing 100 % 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 0 F D EL IRL I L NL P E PO TU LV SLO ES SLK CZ healthcare and social services are considered as core domains of the welfare state. According to recent Eurobarometer surveys, Europeans put the responsibility first on the shoulders of the public sector (72% and 86% for healthcare and social service respectively), well ahead of non-profit organisations (14% and 4%) and private sectors (7% and 6%)165. 10 0 FIN HU Who should provide the care to meet these growing needs? 100 90 DK RO However, socio-demographic changes on the one hand increase demand for social and healthcare and, on the other, constrain the supply of family care. The transforming family structures lead to larger numbers of people living alone, particularly amongst elderly women. In addition, the increasing employment rates of women, in line with the targets of the European Employment Strategy, decreases the availability for providing informal care within the family. Graph 81 In the future, working adults may have to look after their parents more than they do nowadays, 1998 (%) B MT The citizens of the acceding States and candidate countries are more willing to take a greater responsibility in the care of their elderly parents than current EU citizens are. A similar survey to that carried out in the Member States showed that 76% of people in the acceding States and candidate countries expressed positive support, as opposed to 55% in the EU. Interestingly, 81% of the people living in rural areas support this increase in participation in the care for their elderly parents, but only 69% of those who live in the largest cities. The support is also lower for the people with higher education and for managers and white collars as compared to other groups. Furthermore, four out of five EU citizens and 85% of the people who live in the acceding States and candidate countries indicate their preference for social services to assist the elderly in their homes as long as possible, rather than the elderly going into residential care. In other words, community care is preferred to residential care. The 1999 Eurobarometer asked the general public whether older people in need of personal care should receive it in residential/nursing homes or if the social services should help them to remain in their own home as long as possible. The great majority of citizens (9 out of 10 of those who expressed an opinion) stated a preference for home (or community) based care. This is a view shared by policy makers in all Member States. A BG Source: Eurobarometer 2002 At home or in an institution? Don’t know Neither CY S UK EU-15 Source: Eurobarometer 165 See "The Social Situation in the European Union " - 2000. 100 The social dimension of health Section 2 Since the end of the 1970s, the need and demand for social services has grown, due, among other factors, to the ageing of the population, increased female labourmarket participation and the reduction in household size. The transformation of family structures and the increasing activity rates affect the capacity of family members to provide informal care to their dependants. This is true for young children but also for dependant elderly. Graph 83 Areas of non-profit job growth by field, 1990-1995 Social services 32% It was shown in chapter 2.3 that various European countries have attempted to reform their service supplies and increase their overall efficiency, mainly by decentralising powers to local administrations. For example, within the European Employment Strategy, there is a tendency to encourage Member States currently with low childcare provision to increase its availability. However, establishing the conditions for meeting supply and demand for local social services and care is often still problematic. The resulting gap has been partially filled by the families themselves, which have continued in their traditional role as self-producers of services, particularly in Continental and southern Europe. In some cases, the demands for care services led to an increase in underground supply166 and were covered by the development of informal activities utilising casual labour or increasing the use of informal domestic services167. Health 40% Culture and recreation 3% Education 14% Development 5% Other 6% Source: CIRIEC 2000 Europe168. Furthermore, health and social services represented nearly three-quarters of the employment growth in the non-profit sector between 1990 and 1995, with different patterns across the Member States. In the European Employment Strategy, stronger support is being given for the social economy and partnerships as Member States increasingly address the social economy as an important factor for local development, although with widely different understandings of the meaning of social economy Third sector organisations also tried to meet increasing demand for services in social care and welfare. The share of the 'Social economy' is increasing. There are different variants of the structures of the social economy in the Member States. As healthcare and social services are considered core domains of the welfare state, a large part of their activities are governments funded169: In the European Employment Strategy, stronger support is being given for the social economy and partnerships as Member States increasingly address the social economy as an important factor for local development, although with widely different understandings of the meaning of social economy. In the domain of health and care services, the activities of non-profit enterprises (or third sector organisations) are on the increase. These organisations take the forms of cooperatives, associations, mutual organisations and foundations. The initiatives they are involved with tend to develop to cover emerging needs that are not covered by public services or by the market economy. The third sector organisations are able to produce neighbourhood and social services, even with the risk of zero profits. They recover part of the demand that would draw on underground supply and transform part of the self-production (by families) of services into formal supply. Today, these organisations represent a sizeable economic and social reality in many countries: Considering only the paid work in such organisations, the third sector represents 10% of the European economy and 6.6% of civil employment in ● Within the countries of the Continental model (Germany, France, Austria, Belgium, the Netherlands and Luxembourg), the public sector plays an important role in financing provision, but historically the delivery has been in the hands of big charitable or non-profit organisations. For example, in Germany seven large non-profit organisations are largely responsible for social services with public funding. The share of public financing of non-profit healthcare activities is as high 84% in France and Germany. ● In the Mediterranean model (Italy, Spain, Portugal and Greece) the public welfare systems are less developed and a large part of the development of social provision appears to be in conjunction with the development in the social economy. In Italy the share of public financing is 72%. 166 Third System, Employment and Local Development Capitalisation Reports: Key Sectors by Carlo Borzaga, Antxon Olabe and Xavier Greffe – report to European Commission, 1999 167 See "The Social Situation in the European Union"- 2002 for some insight of the importance of migrant workers in the sector of domestic activities. 168 Third system and employment ; a mid term review – Report to European Commission - 2000 (CIRIEC 2000). 169 Role of the social third sector in market economies: a European perspective - Cesar Foundation (1999) for the European Commission. 101 Section 2 The social dimension of health ● Within the Anglo-Saxon model (Ireland, UK), public supply and management prevails, but there is also an important social economy and a very wide range of non-profit organisations: charities, hospitals, universities, the church (Ireland), social co-operatives and pension funds. The share of public financing of non-profit healthcare activities is 23% in the UK. ● In the countries of the Scandinavian model (Denmark, Finland, Sweden), the public sector dominates the supply of social services. The third sector mainly covers the domains of culture, leisure and labour and is only beginning to emerge in the delivery of care services, supported largely by public financing (87% of financing in such healthcare activities in Sweden is public). result from the interaction between the environment and the impairment. The ECHP survey170 provides some information on self-perceived difficulties faced in daily life and the potential need for assistance within the population. In 1996, on average, 4.5% of the EU population reported to be severely hampered and 10% hampered to some extent. In general, women tend to report a slightly higher level of moderate disability than men (10.6% compared to 9.3%) but there is less difference when severe disability is considered. The results, however, have to be interpreted with caution due to the subjective nature of this disability measurement. In other words, variations in disability degrees between Member States may express different linguistic or cultural interpretations of disability among the Member States, rather than actual differences in rates of disability in daily life. The following graph shows that the subjective evaluation of experiencing some restriction due to physical or mental health problems is relatively stable over time, particularly for people declaring severe restrictions. However an increase was observed during the third wave of the ECHP survey in Germany and to a lesser extent in Belgium, as more people declared they "suffer from being hampered to some extent" in these two countries. The rate for severe incapacity is much more stable. The third sector should not only be considered in economic terms as it plays an important role in the creation and reproduction of social capital, by organising opportunities for volunteering or adult education. Volunteering is an important contribution to third sector dynamism: partial data shows that unpaid work is 40% of total work (in full-time equivalent) within the sector in Germany, France and Italy and as high as 73% in Sweden (where recreational and sport related activities have the highest share). The core domains of welfare state (healthcare, education, social services) use 62% of volunteering activities in UK, 58% in Germany, 42% in the Netherlands and Ireland, 28% in Sweden and 19% in Denmark. Graph 84 Hampered in daily activities by any physical or mental health problem, illness or disability - either severely or to some extend 50 40 In democratic societies, the third sector, or the civil society, also contributes to the political debate by encouraging membership and supporting the 'voices' of particular causes. As they pursue a multiplicity of economic and social objectives, they often act as representatives of, and advocates for, citizens and groups, for whom they voice concerns. In addition, they are usually close to groups targeted by public actions and programs. For example, the involvement of representatives of people with disabilities in the implementation and follow-up of policies and actions affecting their lives contributes to the success of these measures. In the field of healthcare and social services, such advocacy activities are represented by growing patient or client movements, particularly elderly care. 2.4.5. 50 1996 1997 1998 - total 40 30 30 20 20 10 10 0 0 EU B DK D EL E F IRL I L NL A P FIN UK Source: ECHP - UDB, 12/2001 The European policy for people with disabilities. In recent decisions, the European Union has developed a human-rights-based approach to disability. This is underpinned by Article 13 of the Amsterdam Treaty, which provides legitimacy for European actions to combat discrimination based, amongst other things, on disability. Within the 'social model of disability', disability is considered as a product of the person's environment and social context, rather than a medical issue or an inherent attribute of the person. Living with disabilities in the EU Chronic physical or mental health problems can hamper participation in daily life. Disability and participation shortcomings should not be considered as constant for a particular impairment, but rather as phenomena that 170 Disability and social participation in Europe, Eurostat 2001.(14 Member States, Sweden excluded). ECHP data proposes a subjective evaluation of disability: people are asked whether they feel severely or to some extend hampered in daily activities, independently from any administrative or medical rating of disability. 102 The social dimension of health Section 2 aged 60 to 64 in 2020 or 2040 will have had a different life history to people currently in this age group. The generational effect on the health conditions, at any given age, will be very important due to profound transformations in lifestyle across Europe. Putting together large series of data corresponding to different industrialised countries tends to show a slightly rising trend in disability-free life expectancy during the last 15 years. The data on life expectancy without severe disability suggests that the increase in life expectancy appears to be combined with a decrease in the most severe disability and an increase in the least severe one171. These results suggest that the level of severity is a key concept when analysing disability trends. This is discussed in more detail in section 2.1. Achieving equal opportunities for people with disabilities requires a multi-pronged strategy aimed at full participation, combating discrimination, facilitating independent living, promoting greater social integration, avoiding poverty and social exclusion, enhancing the opportunities for education, training, lifelong learning and employment and increasing the availability and quality of care and assistive technologies. In short, it is more a question of identifying disabling situations rather than disabled people. Disability increases with ageing... Surveys conducted in all EU Member States have collected systematic information on the link between age and disability and usually present results in two categories: those severely hampered and those hampered to some extent. The prevalence of self-reported disability increases with age at a significant rate. On average only 2.7 % of people aged 25–34 are severely hampered. This proportion reaches 13.9% for the age group 55–64 and further increases to almost 39.1% for people above age 85. The proportion of those moderately hampered increases more rapidly, from 8% in the age group 25 to 34 to 28.8% for the people aged over 85. ...and affects social participation.... Social participation in work, education, voluntary organisations, clubs or trade unions are important activities, which contribute to the quality of life of the individual and to the quality of society. However, too often society may impose physical and attitudinal barriers preventing the full participation of people with disabilities in everyday life. Activities that the rest of society takes for granted may be inaccessible to people with disabilities, hence barriers prevent their full participation in society. Graph 85 Percentage of people hampered in daily activities by any physical or mental health problem, illness or disability, by age. EU, 1998 70 60 Accessibility issues are more important for some groups of people than for others. A recent Eurobarometer survey172 in Member States, which, although it does not specify in great detail the type of physical and mental impairment considered and furthermore the answers are based on very broad stereotypes, is nevertheless informative. The results of the survey showed that 85% of Europeans considered that access to public transport would be difficult for the blind and the physically disabled. The most critical positions were observed in France and Greece. In Sweden, respondents were less critical about the accessibility to services and events, maybe because this country has already tailored a large part of the infrastructure (public and private) to people with disabilities. 70 Hampered to some extent Severely hampered 60 50 50 40 40 30 30 20 20 10 10 0 0 15_24 25_34 35_44 45_54 55_64 65_74 75_84 85_ Source: ECHP - UDB, 12/2001 Overall, 57% considered that access to public places had improved over recent years. The general perception was that public authorities – both local (66%) and national (55%) – have largely been responsible for improving the access over recent years. The voluntary organisations and NGOs are also thought to be providing support and improvements in addressing issues, for which they are not always responsible. This increasing trend with age is observed in all Member States: the highest progression is observed in Finland and the lowest in Italy and Greece. Some researchers anticipate that population ageing, along with the increasing survival rates from disabling accidents and illnesses, will lead to an increase in the proportion of the population with disabilities or chronic illnesses. With increasing life expectancy, prevalence of visual and hearing impairments increases, as well as mental health problems such as Alzheimer's disease and dementia. However, caution is needed when interpreting this data to ensure possible generation effects are correctly integrated. One has to consider that people In the field of education and learning, access to mainstream education for disabled people is difficult. In many cases, segregation begins at an early stage, with disabled children moving into parallel networks of education. This segregation in turn will perpetuate stereotypes, misconceptions and a mutual lack of understan- 171 As expressed by J-M. Robine in "Can we hope for both long life and good health?" 172 Eurobarometer 54.2, 2001. 103 Section 2 The social dimension of health Graph 86 Difficulty of access to services and events for people with disabilities (1 not at all, 2 not very, 3 fairly, 4 very difficult) 2,0 2,5 3,0 3,5 Graph 88 Percentage of being in work among the populations with severe, moderate and no disability, by country and sex, age 16-24, 1996 (both sexes) 4,0 90 Cultural events Universities or schools Physically disabled people Workplaces Blind people Restaurants, hotels Other public services Public transport Deaf people 2,0 2,5 3,0 3,5 moderate no 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 B 4,0 DK D EL E F IRL I L NL A P FIN UK EU-14 Source: 1996 data, taken from ‘Eurostat: Disability and social participation in Europe 2001’ like Finland, France and Austria, which have achieved high rates of employment for their population, manage to maintain high levels of employment for the disabled, particularly for people reporting moderate disability. Conversely, countries such as Greece and Spain, with relatively low levels of employment, provide limited opportunities for disabled people to access the labour market173. Graph 87 Who is respondible for improving access 10 20 30 40 50 60 70 Local authorities National government Voluntary organisations & NGOs Employers/companies Should be responsible The EU Actually responsible In every age group there is a higher probability of people reporting no disability to be in work compared to people with some disability. The gap gets wider in middle age and narrows amongst the elderly. For the group 25 to 29, the employment rate reaches 40.2% for people with severe disabilities and 69.2% for those with no disabilities. The values then decrease continually across all age groups for people with severe disabilities, whereas the highest employment rate is observed at the age 40-45 for people without disability. Considering participation in the labour market, supply and demand effects should be distinguished: if people with disability are limited in the type of activities they can do, they may accept lower wages. Furthermore, the availability of disability benefits increases the minimum wage required by a person to take up a job. Young people with some disability have stronger incentives to work than to live on benefits, considering long term impact on income levels. The trend is different in older groups where work and career opportunities are fewer or less inviting. At the same time, a hostile environment, in terms of barriers and attitudes, may discourage people from being economically active. The attitude of the employers is particularly important: hiring a person with disabilities is too often associated with higher costs, absenteeism, lower productivity and lower mobility174. Efforts to improve accessibility and public transportation, adaptation of the work places and availability of home care are all key factors to increasing economic activity. All of these 0 severe 80 0 Source: Eurobarometer 54.2, 2001 0 90 % Intellectually disabled people Sports events 10 20 30 40 50 60 70 Source: Eurobarometer 54.2, 2001 ding. This can be seen as a dynamic exclusion process, which further strengthens misunderstanding, erroneous attitudes and discrimination. In comparison, the inclusion of disabled people through their school life is one of the most powerful ways to remove stereotypes and negative attitudes towards disabled people for future generations. ... particularly participation in employment.... Employment rates among disabled people fluctuate with the economic cycle, but in general very little increase has been observed since the mid-1980’s. According to the ECHP, the rate of employment of people with a severe disability is only a third of the rate of employment for people without disability, at the European level, with variations between Member States. For people with moderate disability the rate reaches 47% while the values are 66% for the people declaring no disability. However, it is important to note here that disability does not mean inability. Some countries, 173 Further information will be available from the Labour Force Survey, which will include a module people with disabilities that will be undertaken by the European Union in 2002. 174 S. Grammenos, CESEP, 2002, op.cit. 104 The social dimension of health Section 2 People with disabilities are also more likely to suffer economic problems. Comparing socio-economic groups, it seems also that, not only do disadvantaged groups live shorter lives, they also have the highest share of years lived with disabilities. People with disabilities might have extra medical needs, or need specific support in order to be able to live independently. In some Member States people with disabilities are provided with extra support based on the specific needs arising from their disability. The needs assessed are, however, normally related to self-care, with less attention given to support their social or mobility needs. Age is often taken into account when assessing needs; in some Member States the elderly are not entitled to the same range of benefits as the younger disabled. This is particularly the case for mobility, social contacts or skills development needs. Graph 89 Percentage being in work 90 90 80 80 70 70 60 60 50 50 40 40 30 20 10 30 Severe disability Moderate disability No disability 20 10 0 0 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Source: ECHP - EU-14, 1996. As the level of disability reported within the working age-population is much higher above the age of 50, linking the work requirements and the work environment to worker ability may increase employment. New strategies to reintegrate workers after illness or accidents may also increase the employment rate for this group. During the last three decades the European Union has witnessed the expansion of its welfare systems, which include disability benefits, the third largest category after old age benefits and sickness/care expenses. In the early 1990s new public policy techniques were introduced, aimed at the cost containment and cost control of the increasing trends of disability expenditures. In this context it became an increasingly important fact that the elderly, the disabled and the chronically ill represent a significant group with great challenges for new policy interventions. Disability is more prevalent for people in blue-collar occupations, although this may be due to the higher risks to health and safety of blue-collar occupations. The age effect is quite a complex one as it combines the health selection effect with the accumulation of education and experience: Upward professional mobility during working life is more common among people in good health and downward mobility more common among people whose health has deteriorated. On average, 8% of working age Europeans reporting a severe disability have no income (compared to 15% for the people without disability). Conversely, 29% have an earned income and 59% receive an income through a pension or benefit (these figures are 69% and 13% respectively for people without disability). On EU-average, 48% of people with a severe disability receive sickness and disability benefits, this varies from 65% in the UK to 27% in Austria, although this may be due to a certain amount of variation within the definition between Member States. Data presented here should not hide the fact that there are different definitions of disability with reference to different contexts and encompassing different realities in different policy areas. For example, in the area of income maintenance, it means partial or total inability to earn a living; in the area of employment policy, it means reduced productivity or factors leading to discrimination in entering or retaining a job; and in the area of independent living, it means extra needs for self-care and support. As disabling effects vary in different contexts, the impairment assessment is not essential and this questions the possibility of a coherent and stable disability status across the different policy domains. The cost of disability for an individual or a household is seldom comprehensively reported. It should not only include medical expenses, equipment, adaptation of housing, but also the lower income generally received by people reporting disability and any loss of income applicable to a person providing care. For example, a UK study estimated that raising a severely disabled child costs three times as much as a non disabled child. ...and access to adequate services and benefits. Responding to a survey of disabled people in seven Member States175, around 93% of the respondents found that the benefits received were inadequate. This finding is consistent with the reported insufficiency of income to cover basic needs. Subsequently, the majority of disabled people find themselves either in a very poor or poor situation. A high percentage of respondents in the survey indicated the existence of a benefit trap, Another important political issue of note is the increase in needs for care and access related to chronic diseases, particularly when facing the increasing share of chronic diseases in the older age groups. The need for restructuring health and long term care systems in order to better address the modification of the demand due to ageing were analysed in section 2.3 of this report. 175 Yfantopoulos Y (2002) Disability and Social Exclusion in the European Union. Time for change, tools for change (with the support of the European Union and under the auspices of the European Disability Forum). 105 Section 2 The social dimension of health Graph 90 Percentage of people of working age (16-64) receiving sickness or disability benefits Graph 91 Percentage of people declaring to have a long standing illness or disability that limits their activities in anyway 70 35 60 30 50 50 25 25 40 40 20 20 30 30 15 15 20 20 10 10 10 10 5 5 0 0 70 Severe disability Moderate disability No disability 60 0 EU14 B DK EL E F IRL I L NL A P FIN UK 35 Male Female 30 0 BG CY CZ EE HU LV LT MT PL RO SK SL TU Note: Confidential for D Source: ECHP 1996 Source: Eurobarometer on the candidate countries, 2002.1 which prevents disabled people from accessing part or full time jobs, without losing the necessary income support. This is listed as one of the major barriers to participation in employment. to the current Member States, health satisfaction is higher for women (89% satisfied) than for men (64% satisfied). Health satisfaction is highest for the youngest and the oldest age groups (79% for 15 to 24 and 74% for those 55 and over) while it is very low (43%) for the 40 to54 age group. Disability levels in the acceding States. In a survey organised in 2002, people in the acceding States and candidate countries were asked to subjectively evaluate their own health situation on a 4-grade scale (from "very satisfied" to "not at all"). Combining the first stages ("very satisfied" to "fairly satisfied"), the three Mediterranean acceding States and Slovenia rate their health the most positively. Non-satisfaction is highest in Romania, Hungary and Bulgaria. As opposed Across all acceding States and candidate countries, one quarter of the population declare that they suffer from some form of long-standing illness or disability, restricting their activity. Hungary, Poland and the Czech Republic are among the countries where this subjective self-assessment of disability is the worst, while the lowest level of disability is reported in Malta176. 176 These data should not be compared directly to the disability levels measured in the Member States through the ECHP because both surveys have different designs and methodology. 106 Areas of social policy concern - statistical portraits Section 3 Section 3 Areas of social policy concern - statistical portraits 107 Section 3 Areas of social policy concern - Statistical portraits Areas of social policy concern - statistical portraits Section Three presents a series of statistical portraits that address a range of social policy concerns for the European Union. Virtually all the main European social policy domains are covered: population; education and training; labour market; social protection; income, poverty and social exclusion; gender equality and health and safety. Each statistical portrait is presented in the form of tables, graphs and commentary. This year's report includes twenty-two portraits, one more than last year. The new portrait “Labour Market Policy expenditure” is added in the domain “Social protection”. It is also strongly linked with the domain “Labour market”. Gender issues are covered not only by the three portraits in the domain “Gender equality” but also by other portraits and the statistical annexes where a number of indicators are disaggregated by sex. Each portrait (apart from the two first portraits which provide contextual information, one on the economic situation, the other on demography, households and families) is built around one (or two) selected key indicator(s) : see following table. Together, this set of key indicators provides not only a snapshot of today's social situation but also an instrument for monitoring and comparing progress in the social field among the fifteen Member States and the Acceding/Candidate Countries. The following criteria have been applied as much as possible in selecting the key indicators: 1) Each indicator should be: i) policy relevant at EU level ii) comparable across the fifteen Member States iii) available using Eurostat harmonised sources iv) measurable over time and v) easily understood. 2) The set of indicators should be relatively stable over time to ensure continuity. However, a degree of flexibility is required to take account of changing policy needs and -improvements in data availability. Fifteen of the twenty-four key indicators are among the structural indicators within the Spring Report 2003 (COM(2003) 5 final, 14.1.2003), which the Commission has prepared for the Spring European Council (21.3.2003) on the Lisbon strategy of economic, social and environmental renewal. A summary of the key indicators with data for each Member State can be found in Annex I. Detailed statistical data covering the whole report can be found in Annex II. The Annexes III and IV present key statistical data on social trends for the acceding States and Candidate Countries. They correspond as much as possible to the Annexes I and II. Symbols, countries and country groupings, other abbreviations and acronyms are explained in Annex V. The editing of the portraits has ended in March 2003. Additional or more recent data can be requested from Eurostat Datashops (see list in Annex VI). 108 Areas of social policy concern - Statistical portraits Section 3 Domain Statistical Portrait Selected key indicator(s) Economy 1 Economic situation - Population 2 3 4 Demography, households and families Ageing of the population Migration and asylum Old age dependency ratio Net migration rate 5 6 Education and its outcomes Lifelong learning Early school-leavers Lifelong learning (adult participation in education and training) Employment Employment rate Employment of older workers Employment rate of older workers (55-64) and Effective average exit age Unemployment rate Youth unemployment/population ratio Long-term unemployment rate Education and training Labour market 7 (see also the portraits nr. 14, 19 and 20) 8 Social protection 9 10 11 Unemployment Youth unemployment Long-term unemployment 12 Social protection expenditure and receipts 13 Social benefits 14 Labour Market Policy expenditure Income, poverty and social exclusion 15 16 Gender equality Inequality of income distribution At-risk-of-poverty rate before social transfers and At-risk-of-poverty rate after social transfers Population in jobless households – persons aged 0-65 and Population in jobless households – persons aged 0-60 17 Jobless households and low wages 18 19 20 Women and men in decision making Employment of women and men Earnings of women and men Female share in national Parliaments Female and male employment rates Gender pay gap in unadjusted form Life and health expectancies Life expectancy at birth and Healthy life years Accidents at work – serious accidents and Accidents at work – fatal accidents Health and safety 21 22 Notes: Income distribution Low-income households Social protection expenditure as a percentage of GDP Old age/survivors benefits as a percentage of total social benefits Active public expenditure in LMP as a percentage of GDP Accidents and work-related health problems No key indicator has been chosen for either of the contextual statistical portraits (numbered 1 and 2). Those indicators used as structural indicators within the Spring Report 2003 are written in italics. 109 Section 3 Areas of social policy concern - Statistical portraits 1 Economic Situation Weak economic growth in 2001, slow recovery in the first half of 2002 In 2001, the European Union’s gross domestic product rose by 1.5%, which means a significant slowdown compared to the previous year (3.5% in 2000). Among the four biggest Member States, the United Kingdom recorded the highest rate of growth (1.9%), followed closely by France and Italy (1.8% each). Germany showed weak growth of only 0.6%, which was lowest not only among the four biggest economies, but among all the fifteen Member States. However, all four saw slowdowns in their GDP growth rates in 2001; this effect being more marked in Germany and France than in the United Kingdom and Italy. In 2001, as in the year before, Ireland recorded growth well above that in the other Member States: Ireland’s GDP expanded by 5.9%, followed by Greece at 4.1% and Luxembourg at 3.5%. Among these three, Ireland and Luxembourg saw significant slowdowns when compared to the growth rates of 2000. With growth rates of 2.8% Spain was behind the three countries mentioned, but still ahead of the average in 2001. All other Member States are grouped together in a quite narrow range, with Germany and Finland marking the lower end at 0.6% and 0.7% growth, respectively. All EU Member States, with the exception of Greece, recorded growth rates below those of 2000: the biggest slowdowns were recorded in Ireland, Finland and Luxembourg. Examining, however, the development over the four quarters of 2001, it can be seen that growth was still healthy in the first quarter, but dropped to near zero in the middle of the year and finally turned out to be negative (on a quarter-to-quarter basis) in the fourth quarter. Concerning the first two quarters of 2002, growth rates were very modest but back in positive territory. During the second quarter, GDP growth was observed to be +0.7% compared to the same quarter of the previous year for the European Union and +0.6% for the eurozone. GDP per head variations between Member States remain substantial In 2001, GDP per capita for each citizen in the European Union amounted to 23,200 PPS, slightly above the figure for the euro-zone (23,100 PPS). The highest figures occurred in Luxembourg (44,300 PPS), Ireland (27,700 PPS) and Denmark (27,600 PPS), the lowest in Greece (15,500 PPS) and Portugal (17,100 PPS). To make comparisons among Member States easier, GDP per capita may 110 be given in relation to the EU average (EU-15 = 100). This figure for Luxembourg is a remarkable 91% above the EU average. The second highest figures are those of Ireland and Denmark, but here the difference is only 19%. The biggest differences for figures below the EU average are in Greece (33% below average), Portugal (–26%) and Spain (–17%). Compared to the situation in 1995, it can be seen that the positions at the extremes remain unchanged, even if the three lowest ranking countries have moved somewhat closer to the EU average. The most obvious change was for Ireland, which recorded a figure for per capita GDP that was lower than the EU average in 1995, while in 2001 it was 19% above average, placing Ireland second among all EU Member States. Moderate inflation In July 2002, EU-15 annual inflation was 1.8% and eurozone annual inflation 2.0%. A year earlier the corresponding rates were 2.5% and 2.6% respectively. Among Member States, highest annual rates were in Ireland (4.2%), the Netherlands (3.8%) and Greece and Portugal (3.6% each) in July; lowest rates were in Germany (1.0%), the United Kingdom and Belgium (1.1% each). Compared with July 2001, annual inflation rose in two Member States, remained unchanged in one and fell in twelve. The only relative rises compared to July 2001 were in Spain (2.4% to 3.5%) and Ireland (4.0% to 4.2%); the biggest relative falls were in Belgium (2.7% to 1.1%), Germany (2.6% to 1.0%) and the Netherlands (5.3% to 1.8%). Since the beginning of 2002 the figures have shown an overall downward trend and in June 2002, the annual rate of change of the euro-zone has passed below the 2.0% stability threshold defined by the ECB for the first time since May 2000. The 12-month average rate of change in consumer prices, which is less sensitive to transient effects, stood at 2.1% for the EU-15 and at 2.3% for the eurozone. Both rates are, in fact, only slightly higher than the 2.0% -medium-term price stability threshold. Interest rates at a low level The general trend in long-term interest rates in the EU in 2000 and 2001 was downwards. However, in December 2001 and the first quarter of 2002 rates tended to rise, before easing again. In August 2002 the aggregate interest rate for the euro-zone, as measured by 10-year government bond yields, stood at 4.80% (monthly average), compared with an annual average of 5.03% in 2001, and 5.44% (excluding Greece) in 2000. Areas of social policy concern - Statistical portraits Section 3 The most distinguishing feature is, however, the high degree of convergence achieved. Up to the start of 1999, when the third phase of monetary union began, the yield differentials on 10-year bonds among eurozone members narrowed sharply and almost disappeared. Since then, yields have been at broadly similar levels. Before the addition of Greece to the euro-zone in January 2001, the differential between Greece and the rest of the euro-zone also narrowed sharply. In August 2002 the differential between Germany (the euro-zone member which normally has the lowest interest rates) and Greece (which has the highest rates) was 62 basis points. The three EU Member States not participating in the single currency yields have been at broadly similar levels to those of the euro-zone. In August 2002 UK yields were 13 basis below those of the euro-zone, and those of Denmark and Sweden slightly above. are three of the four largest economies of the European Union – the deficit was below the reference value of 3% of GDP. Nevertheless it cannot be neglected that four countries (Portugal, Italy France, and Germany) which had managed to constantly enhance their budgetary situation since 1996 faced a trend reversal in 2001. The euro-zone and the EU-15 have, broadly speaking, shown a parallel development. While the deficit was reduced steadily since 1995 and had disappeared in 2000 it rose in 2001 for the first time in the period examined, reaching 1.3% of GDP in the euro-zone and 0.6% in the EU-15. These figures suggest that the year 2001 saw a certain drawback from the efforts to balance government budgets in the Community. Public debt is defined in the Maastricht Treaty as consolidated general government gross debt at nominal value, outstanding at the end of the year. At the end of 2001, eleven countries had a level of public debt below the 60% threshold, Germany and Spain having fallen below in the course of 2001, while Austria was only slightly above. Three Member States — Italy, Belgium and Greece — were still above or close to 100%, but their figures have been falling every year since 1995. At the end of 2001, the average debt ratio for the 15 Member States stood at 63.0%, with a figure of 69.1% for the countries in the euro-zone. The general reduction of public debt continues despite worsening public deficit Public deficit is defined in the Maastricht Treaty as general government net borrowing according to the European system of accounts. In 2001, eleven (compared to nine in the previous year) Member States achieved a budget surplus (net lending) or a balanced budget, while for all the others – among which, however, Policy context results of the Barcelona European Council of March 2002. In addition, the BEPGs are based upon the Report on the Implementation of the 2001 BEPGs that gives an account of how well the 2001 and earlier Broad Economic Policy Guidelines have been carried out. (Both the 2002 BEPGs and the report on the implementation of the 2001 BEPGs are available at europa.eu.int/comm/economy_finance/publications/.) The BEPGs for 2002 recommend that action concentrate on four areas: In order to participate in the euro area, Member States must fulfil legal convergence and the convergence criteria on price stability, government budgetary position, exchange rate and interest rate. On 22 May 2002, the European Commission adopted the 2002 Convergence Report, in which convergence progress made by Sweden is examined in accordance with Article 122(2) of the Treaty. As the other two Member States not participating in the euro area, Denmark and the United Kingdom, negotiated opt-out clauses before the adoption of the Maastricht Treaty, they are not dealt with in the report. The report concludes that Sweden fulfils three of the convergence criteria (on price stability, the government budgetary position and convergence of interest rates) but does not fulfil the exchange rate criterion. Moreover, central bank legislation in Sweden is assessed not to be compatible with the Treaty and the Statute of the ESCB. In the light of this assessment the Commission concludes that there should be no change in the status of Sweden as a Member State with derogation. ● ● ● ● safeguarding macroeconomic stability; promoting more and better jobs, raising labour force participation and employment, as well as addressing persistent unemployment; strengthening conditions for high productivity growth; and promoting sustainable development in the interest of current and future generations. The BEPGs consist of two parts. The first part comprises horizontal recommendations, which are general and apply to all individual Member States. The second part consists of country-specific guidelines that take into account the particular circumstances of each Member State and the different degree of urgency of measures. Covering both macroeconomic and structural policies, the BEPGs are at the centre of the EU economic policy co-ordination process, and constitute the reference for the conduct of economic policies in the Member States. On 24 April 2002, the Commission adopted its recommendation for the 2002 Broad Economic Policy Guidelines (BEPGs) for the economic policies of the Member States and the Community, in line with article 99(2) of the Treaty. The 2002 BEPGs extend the strategy set out to meet the objectives of the Lisbon and Stockholm European Councils, to take account of the 111 Section 3 Areas of social policy concern - Statistical portraits Methodological Notes All National Accounts figures are in line with the European System of National and Regional Accounts in the Community (ESA95). ESA95 is the subject of Council regulation No 2223/96 of June 25, 1996. Gross domestic product indicates the size of a country’s economy in absolute terms, while GDP in relation to the population (GDP per capita) provides an indication, albeit somewhat simplistic, of a country’s wealth. To make international comparisons easier, data are expressed in purchasing power standards (PPS). The advantage of using PPS is that they eliminate distortions arising from the different price levels in the EU countries: they don't use exchange rates as conversion factors, but rather purchasing power parities calculated as a weighted average of the price ratios of a basket of goods and services that are homogeneous, comparable and representative in each Member State. Consumer price inflation is best compared at international level by the ‘harmonised indices of consumer prices’ (HICPs). They are calculated in each Member State of the European Union, Iceland and Norway and also in most Candidate Countries. HICPs are used by the European Central Bank for monitoring inflation in the economic and monetary union and the assessment of inflation convergence. As required by the Treaty, the maintenance of price stability is the primary objective of the European Central Bank (ECB) which defined price stability ‘as a year-on-year increase in the harmonised index of consumer prices for the euro-zone of below 2%, to be maintained over the medium term’. A more stable measure of inflation is given by the 12-month average change, that is the average index for the latest 12 months compared with the average index for the previous 12 months. It is less sensitive to transient changes in prices but it requires a longer time series of indices. 112 Depending on whether or not a country’s revenue covers its expenditure, there will be a surplus or a deficit in its budget. If there is a shortfall in revenue, the government is obliged to borrow. Expressed as a percentage of GDP, a country’s annual (deficit) and cumulative (debt) financing requirements are significant indicators of the burden that government borrowing places on the national economy. These are in fact two of the criteria used to assess the government finances of the Member States that are referred to in the Maastricht Treaty in connection with qualifying for the single currency. Government bond yields are a good indicator of longterm interest rates, since the government securities market normally attracts a large part of available capital. They also provide a fairly good reflection of a country’s financial situation and of expectations in terms of economic policy. The significance of government bond yields as a measure of Economic and monetary union is recognised in the Treaty on European Union, where it appears as one of the criteria for moving to stage three of monetary union. Links to other parts of the report Employment (3.7), Unemployment (3.9), Economy (Annexes II and IV). Further reading ● ● ● Economic Portrait of the European Union 2002, Eurostat The EU Economy: 2001 Review, DG Economic and Financial Affairs Publications on national accounts, consumer prices and interest rates are available from the "Statistics in focus" collection on Eurostat's web-site (europa.eu.int/comm/eurostat). Areas of social policy concern - Statistical portraits Section 3 Key indicator EU-15 EU-12 B DK D EL E F IRL I L GDP growth rate (Growth rate of GDP at constant prices (base year 1995). Annual and year on year quarterly growth rates) 3.4 1.5 0.4 0.7 1990 1995 2000 2001 2010 3.5 1.5 0.3 0.6 4.0 1.0 -0.3 0.3 3.0 1.0 1.1 1.9 2.9 0.6 -0.2 0.1 4.2 4.1 4.3 4.0 4.1 2.8 2.0 2.0 3.8 1.8 0.4 1.0 11.5 5.9 0.1 2.9 2.9 1.8 0.0 0.2 7.5 3.5 : : NL A P FIN S UK 3.3 1.3 0.4 0.1 3.0 1.0 0.0 0.9 3.5 1.7 1.4 : 6.1 0.7 -1.7 2.5 3.6 1.2 1.0 1.6 3.1 2.0 1.0 1.3 Note: Quarterly growth rates are in comparison to the same quarter of the previous year and are based on seasonally adjusted data, except for Ireland. Source: Eurostat - Demographic Statistics. Graph 1 GDP per capita in PPS (index Eu-15=100) Graph 2 200 200 Inflation rate (harmonised indices of consumer prices (HICPs). Annual average rate of change), April 2002 (in%) 5 5 191 4,6 180 4,4 5 180 5 2001 1995 160 4 160 3,8 4 3,7 4 4 140 140 3,0 3 3 2,6 119 120 100 119 112 112 3 120 106 105 2 100 100 100 100 100 83 74 60 EUR 11 L IRL DK NL A B I D FIN F S UK E P 67 1,9 3 1,9 1,8 1,7 2,3 2 1,7 2 80 80 2,3 2,2 2,1 104 103 2,3 60 1,2 1 1 1 0 0 EL EU-15 EUR-12 B Source:Eurostat - National accounts. DK D EL E F IRL I L NL A P FIN Source: Eurostat - 1995-based (baseline) household projections 113 2 1 S UK Section 3 Areas of social policy concern - Statistical portraits 2 Demography, households and families 380 million inhabitants in the Union On 1st January 2002 the population of the European Union stood at almost 380 million. It has the third largest population in the world after China (1,279 million) and India (1,038 million), but ahead of the United States (279 million) and Japan (127 million). Germany has the largest population within the EU. Its 82 million inhabitants make up 22% of the Union's population while the United Kingdom, France and Italy each account for 1516% of the total. Around 17% of the EU-15 population are less than 15 years of age. Ireland has the youngest population (22% of the total). Persons of working age (15-64) account for 67% of the EU total. The remaining 16% are aged 65 and over. The number of elderly people has increased rapidly in recent decades. This trend is expected to continue in the coming decades. See Ageing of the population (3.3). There has been a gradual slowing down of population growth in the Union over the last 35 years. Over the period 1995-2001, the population increased on average by 3.1 per 1000 population per year compared with an annual average of around 8 in the 1960s. Since the mid1980s, international migration has rapidly gained importance as a major determinant of population growth. See Migration and Asylum (3.4). age at which people first get married has also increased: for men, from 26 years in 1980 to over 30 today and for women, from 23 to 28 years. Looking at marriage cohorts, the proportion of divorces is estimated at 15% for marriages entered into in 1960. For those more recently married couples (1980), the proportion has doubled to 28%. There are however considerable differences between countries with more than 40% of marriages (entered into in 1980) ending in divorce in Denmark, Finland, Sweden and the United Kingdom compared with 15% or less in the southern Member States. A marked increase in non-marital unions… In the last decades, conjugal life in many countries has increasingly taken the form of cohabitation. In 1998 EUwide, 33% of young people (under the age of 30) living in a couple and 8 % of all couples were cohabiting. There are wide disparities across countries. While in the Nordic Member States, the Netherlands and the United Kingdom these figures were 53-70% and 13-23%, they were 8-15% and 1-5% in the southern Member States. … and, as a result, a rise in births outside marriage According to the Eurostat baseline scenario (1999 revision), total EU population should peak around 2022. Within the Union, future population growth will be far from uniform. Italy's population is expected to decline early in this decade while Ireland's population is not expected to fall until 2048. The proportion of births outside marriage continues to increase, basically reflecting the growing popularity of cohabitation: from 6% of all births in 1970 to over 28% in 2001. In Sweden, more than half (56%) the children born in 2001 had unmarried parents. The proportion is around 40% in several other countries (Denmark, France, Finland and the United Kingdom). In contrast, low levels, albeit increasing ones, are seen in many southern European countries, including, for example, Greece (1.5% in 1980 to 4.1% in 2000), Italy (4.3% to 9.6% in 2000) and Spain (3.9% to 17.0% in 2000). Fewer children and later in life Trend towards smaller households with … The completed fertility of post war generations has been steadily declining since the mid-1960s, but the total fertility rate remains relatively stable at 1.47, slightly lower than in 2000 due to an estimated decline in births of 1% in 2001. The completed fertility changes far less abruptly over time and is now around 1.7, still well below the reproduction level (2.1 children per woman). See Ageing of the population (3.3). The result of these and other trends (such as the increasing number of people living alone) is that households are becoming smaller and alternative family forms and non-family households are becoming more widespread. Although this pattern can be observed throughout the Union, there are significant variations between Member States. Fewer and later marriages and more marital breakdowns In 2001, there were only 5 marriages per 1,000 inhabitants in EU-15 compared with almost 8 in 1970. The average 114 While the absolute number of households has increased, the average household size has decreased. In 2001, there were an estimated 372 million people living in 156 million private households within the fifteen Member States. This represents an average of 2.4 people per household compared with 2.8 in 1981. Every EU country Areas of social policy concern - Statistical portraits Section 3 has experienced a decline in its average household size over this period. Only Spain, Ireland and Portugal have 2.9-3.0 people per household. in 19901. The overwhelming majority of these lone adults are women. … more people living alone … … and a fall in the number of couples with children In 1999, an estimated 11% of the population were living alone compared with 8% in 1981. The proportion of people living on their own is highest in Finland (18%) and Germany (16%) and lowest in Spain (5%) and Portugal (4%). There are marked differences between the sexes and across generations regarding the share of the population living alone. Women aged 65 and over account for more than one-third of all one-person households, while men of the same age account for only 9% of the total. In parallel with the above changes, the share of the population living in private households composed of two or more adults and dependent children is gradually declining: from 52% in 1988 to 46% in 2000. The highest proportions can be observed in Spain, Ireland and Portugal, due largely to the sizeable proportion (around 20%) of the population living in families with three or more adults and dependent children. However, in Spain and Portugal this proportion has declined dramatically, from just under 30% in 1988. … and a striking rise in the number of children living with one adult … Although the proportion of the population living in private households consisting of one adult and at least one child is relatively small (4%), there has been a marked increase in the number of such households over the last decade. In 2000, 10% of children aged 0-14 years (living in private households) were living with just one adult (a person at least 15 years old) compared with 6% in 1990. In 2000 the proportion ranged from 3% in Greece and Spain to 20% in the United Kingdom, where it was 12% People living in households composed of two adults without dependent children represent 24% of the population although the data include couples whose children may have already left home or children who are still at home but are no longer 'dependent'. The latter account for part of the 14% of the population living in households composed of three or more adults without dependent children. Other examples of this category are households where one or more of the parents of a couple is/are living in the couple's home. This type of household is more common in the southern Member States. See Annex II for data per Member State. Methodological notes Further reading Sources: Eurostat - Demographic Statistics. 1999-based (baseline) Eurostat demographic and household projections. European Community Household Panel (ECHP) UDB, version September 2001 and European Labour Force Survey (LFS). ● ● ● Links to other parts of the report Ageing of the population (3.3), Migration and Asylum (3.4), Population (Annexes II and IV) 1 No data available for the Nordic Member States. 115 “European social statistics - Demography”, 2002 edition. Eurostat. Statistics in Focus (Population and social conditions): "First results of the demographic data collection for 2001 in Europe", No.17/2002. Eurostat. "Family Structure, Labour Market Participation and the Dynamics of Social Exclusion", European Commission DG Research report 2000. "Social Strategies in Risk Societies - SOSTRIS", DG Research report 1999. Section 3 Areas of social policy concern - Statistical portraits Key indicator EU-15 EU-12 B 379 601 305 209 10 307 Total population, 1.1.2002 Percentage share of total EU population 100,0 80,4 2,7 DK D EL E F IRL I L NL A P FIN S 5 368 82 431 10 598 40 409 59 344 3 884 58 018 446 16 100 8 140 10 336 5 195 8 909 2,8 10,6 15,6 1,0 15,3 0,1 4,2 2,1 2,7 1,4 2,3 1,4 21,7 Source: Eurostat - Demographic Statistics. Graph 3 Demographic trends by age-group, EU, 1980-2020 Graph 4 25 Population living in private households by household type, EU-15, 1999 25 20,9 20 19,1 17,9 1980-2000 2000-2020 15 10,3 15 11,8 8,6 10 5,2 5 0 0-14 15-29 30-49 65+ 1 adult living alone 11 % 10 2 adults with dependent children 35% 5 0 50-64 2 adults without dependent children 21 % 80+ -5 -5 -6,5 -10 -15 3 or more adults with dependent children 14 % 20 -7,6 -10 -8,9 -11,8 -13,9 -20 Lone parent with dependent children 3% -15 3 or more adults without dependent children 15 % -20 Source:Eurostat - Demographic Statistics and 1999-based Eurostat demographic projections Source: Eurostat - European Community Household Panel - UDB, version December 2002. No data for S. 116 UK 60 114 15,8 Areas of social policy concern - Statistical portraits Section 3 3 Ageing of the population In 2001, there were 62 million elderly people aged 65 and over in the EU, compared with only 34 million in 1960. Today elderly people represent 16% of the total population or 24% of what is considered to be the working age population (15-64 year olds). By 2010, the latter ratio is expected to rise to 27%. Over the next fifteen years, the number of 'very old' people aged 80 and over will rise by almost 50%. Low fertility levels, extended longevity and babyboomers’ ageing mean that the EU population is ageing It is worth noting that the population aged 55-64 will also grow considerably (around 20%) over the next fifteen years, with rises of more than 40% in France, Ireland, Luxembourg and the Netherlands. Only Germany and Italy will experience an increase of less than 10% although the number of people in this age group is set to rise sharply in subsequent years. See also Employment of older workers (3.8). Three driving forces are behind the ageing of the population: fertility below replacement levels, a fall in mortality and the approach of the baby-boomers to the retirement age. Fertility seems to have reached its lowest point in 1999, with the lowest post-war number of births of just under 4 million. Almost 60,000 more babies were born in the EU in 2000. The total fertility rate for the EU increased from 1.45 children per woman in 1999 to 1.47 in 2001, but this is still low compared to 2.59 in 1960. Countries with the highest fertility at the beginning of the 1980s (Greece, Spain, Ireland and Portugal) are those where it has subsequently fallen the most (by 32-46%). Today, the total fertility rate is lowest in Italy (1.24) and Spain (1.25). Ireland continues to record the highest rate (1.98), together with France, were the rate increased from 1.79 to 1.90 in the last two years. Meanwhile, life expectancy has increased over the last 50 years by about 10 years in total, due to higher socio-economic and environmental conditions and improved medical treatment and care. See portrait “Life and health expectancies” (3.21). Dwindling 'demographic' support for older citizens In 1990, the EU-15 population aged 65 and over corresponded to 21.6% of what is considered to be the working age population (15-64 years). In 2001, this old age dependency ratio had risen to 24.6%. All Member States are expected to see an increase in this ratio between now and 2010 (to an EU average of 27.3%) although the extent of the rise will vary considerably between Member States. Greece, Germany and Italy will experience the most significant change: by 2010, all three countries are expected to have a ratio of around 30%. Meanwhile, Ireland will continue to have the lowest ratio of old people to the working age population (around 17%). Between 1960 and the present day, the proportion of older people (65 years and over) in the population has risen from 11% to 16%. All the signs are that this trend will continue well into the new century although in the course of this decade, the rate of change will be somewhat slower due to the drop in fertility during the Second World War. Nevertheless, by 2010, there will be twice as many older people (69 million) than in 1960 (34 million). Of the 69 million, 40 million will be women. On average, 45% of the 'very old' population will live alone in 2010 In 2010, around one-third (32%) of the Union's elderly population (aged 65 and over) will be living alone. More than half (54%) will live with a partner (in a household that may also include children or adults). The remainder will live with their children (or other relatives/friends) or in a home/institution. It is clear however that the demand for housing and care changes considerably as people grow older. Thus, the elderly should not be regarded as a single age-group. While 63% of those aged 65-79 will live with a partner, only 31% of the 'very old' (aged 80 and over) will do so. The 'very old' will continue to have a greater tendency to live alone (45%), in collective households (10%) or together with their children/other relatives/friends (14%). There are marked differences between countries, particularly regarding the proportion of 'very old' people living without a partner but with their children or other relatives/friends: 30% or more have this form of potential support in Spain and Portugal compared with 5% or less in Denmark, Netherlands and Sweden. In Denmark and Sweden, more than 60% of those aged 80 and over live alone. Over the next fifteen years, the population aged 65 and over will increase by 22%. Growth will be over 30% in Ireland, Luxembourg, Netherlands and Finland. It will remain below 20% in Belgium, Spain, Portugal and the United Kingdom. Population growth fastest among the 'very old' The growth of the population aged 80 or more will be even more pronounced over the next fifteen years: numbers of 'very old' people will rise by almost 50% to over 20 million people EU-wide (of which 13 million will be women). The rise will be as high as 70% in Greece. In sharp contrast, growth will be negligible (below 10%) in Denmark and Sweden. 117 Section 3 Areas of social policy concern - Statistical portraits Policy context In its Communication "Towards a Europe for all ages Promoting Prosperity and Intergenerational Solidarity" (COM 1999 221 final), the Commission concluded that "the very magnitude of the demographic changes at the turn of the 21st century provides the European Union with an opportunity and a need to change outmoded practices in relation to older persons. Both within labour markets and after retirement, there is the potential to facilitate the making of greater contributions from people in the second half of their lives. The capacities of older people represent a great reservoir of resources, which so far has been insufficiently recognised and mobilised. Appropriate health and care policies and services can prevent, postpone and minimise dependency in old age. Furthermore, the demand for these services will open up new job opportunities." The Commission will explore the possibilities for new, horizontal Community action programmes based on articles 13, 129 and 137 of the EC Treaty for those groups of people affected by discrimination, unemployment or social exclusion such as older people. Furthermore under Article 166 of the Treaty, the European Union’s fifth framework programme for Community research will mobilise Europe’s research resources in order to improve the quality of life, autonomy and social integration of older people. Moreover, the Commission is about to adopt its draft for the joint report on how to increase labour force participation and promote active ageing, requested by the Stockholm European Council in March 2001. In order to address the demographic challenge of an ageing population of which people of working age constitute an even smaller part, the Stockholm European Council agreed also to set an EU target for increasing the average EU employment rate among older women and men (55-64) to 50% by 2010. Extended lifelong learning opportunities should be 118 created for supporting the ageing part of the population in an independent and healthy lifestyle, as long as possible and for extending their social network, reinforcing their active citizenship rights in all areas of every day life and avoiding social exclusion. Methodological notes Sources: Eurostat - Demographic Statistics. 1999-based (baseline) demographic and 1995-based (baseline) household scenarios. The old age dependency ratio shows the population aged 65 and over as a percentage of the working age population 15-64. Links to other parts of the report Demography, households and families (3.2), Employment of older workers (3.8), Old age benefits (3.13), Life and health expectancies (3.21), Population (Annexes II and IV) Further reading ● ● ● ● “European social statistics - Demography”, 2002 edition. Eurostat. Statistics in Focus (Population and social conditions): "First results of the demographic data collection for 2001 in Europe", No.17/2001. "First demographic estimates for 2001", No.19/2001. Eurostat. "Towards a Europe for all ages - promoting prosperity and intergenerational solidarity", COM(99)221 final. 1999. "Family Structure, Labour Market Participation and the Dynamics of Social Exclusion", European Commission DG Research report 2000. "Social Strategies in Risk Societies - SOSTRIS", DG Research report 1999. Areas of social policy concern - Statistical portraits Section 3 Key indicator EU 15 B DK D EL E F IRL I L Old age dependency ratio (Population aged 65 and over as a percentage of the working age population (15-64) on 1 January) 21.6 23.0 24.3 : 27.3 1990 1995 2000 2001 2010 22.1 23.8 25.5 25.7 26.7 23.2 22.7 22.2 22.2 24.6 21.6 22.5 23.9 24.5 30.3 20.4 22.8 25.6 : 29.2 20.2 22.3 24.6 24.7 26.8 21.1 23.0 24.6 24.8 25.5 18.6 17.8 16.8 16.6 17.3 21.5 24.1 26.6 27.1 31.3 19.3 20.6 21.4 21.5 23.6 NL A P FIN S UK 18.6 19.3 20.0 20.1 22.3 22.1 22.4 22.9 22.9 26.3 20.0 21.6 23.8 24.2 24.5 19.8 21.1 22.2 22.4 24.9 27.7 27.4 26.9 26.8 28.1 24.0 24.3 23.9 : 24.2 Source: Eurostat - Demographic Statistics. Graph 5 Old age dependency ratio 2001 and 2010 Graph 6 35 70 30 60 25 25 50 20 20 40 35 30 % 2001 2010 Elderly population by household situation and age, EU-15, 2010 % 63 65-79 80 and over 70 60 50 45 40 31 15 15 30 10 10 20 27 30 14 10 5 5 10 0 0 8 20 10 2 0 EU-15 B DK D EL E F IRL I L NL A P FIN S 0 Living with partner only UK Source:Eurostat - Demographic Statistics. EU-15, EL and UK 2000 data. Living alone Living in a collective household Other Source: Eurostat - 1995-based (baseline) household projections 119 Section 3 Areas of social policy concern - Statistical portraits 4 Migration and asylum Since 1989, net migration has been the main component of annual population change in the Union. In 2001, the annual net migration rate was 3.1 per 1 000 population, representing around 74% of total population growth. In 2000, around 5% of the EU population were non-nationals (3.4% were non-EU nationals and 1.5% EU nationals), and there were just over 363,000 asylum applications in the fifteen Member States. Important role of international migration in population growth Since the mid-1980s, international migration has rapidly gained importance as a major determinant of population growth, contributing 72% of the increase in the last five years. This represents just over 880,000 people per annum. Without positive net migration the populations of Germany and to a smaller extent of Greece and Sweden would be in decline. Almost 19 million non-nationals in the EU, of whom 13 million are non-EU nationals The total number of non-nationals living in the fifteen Member States in 2000 was around 18.8 million, the equivalent of 5.0% of the total population. In 1990, the comparable figure was 4.1%. Belgium, Germany and Austria have sizeable non-national populations (around 9%). Next come France and Sweden with about 5.5%. Luxembourg is a unique case with non-nationals accounting for just over one-third of the population. Differences between countries in terms of non-national populations partly reflect differences in national legislation on the acquisition of citizenship. Among the non-nationals, around one-third (six million people) are citizens of another EU Member State and the remaining two-thirds are citizens of countries outside the Union. Belgium, Ireland and Luxembourg are the only countries where other EU nationals outnumber non-EU nationals. The two largest groups of non-nationals living in the Union are Turkish citizens (around 2.4 million in 2000, of Policy context The Treaty of Amsterdam introduced a new Title IV (Visas, asylum, immigration and other policies related to free movement of persons) into the EC Treaty. It covers the following fields: free movement of persons; controls on external borders; asylum, immigration and safeguarding of the rights of third-country nationals; judicial cooperation in civil and criminal matters and administrative cooperation. The Treaty of Amsterdam thus establishes Community competence in the fields of immigration and asylum. The European Council at its meeting in Tampere in 120 whom 2.0 million in Germany) and citizens of the former Republics of Yugoslavia (around 1.8 million, of whom 1.2 million in Germany). Around 1.2 million recorded immigrants into the EU in 1999 were non-EU citizens In 1999, the number of people recorded as migrating into the fifteen Member States was estimated at just over 2.0 million. Around 1.2 million were citizens of a non-EU country. Germany recorded the highest immigration flow of non-EU nationals (539,000), followed by the United Kingdom (177,000) and Italy (123,000 in 1997). 363,100 asylum requests in the EU in 2000 After peaking at 672,400 in 1992, the number of asylum applications in the EU fell to 227,800 in 1996. Thereafter, the trend is upwards. In 2000, an estimated 363,100 requests for asylum were made in the EU, a rise of around 3% on the 1999 figure. The largest increases (in absolute terms between 1999 and 2000) took place in the United Kingdom (+9,157) and Belgium (+6,899). In 2000, the United Kingdom received the largest number of applications (80,315) followed by Germany (78,563), the Netherlands (43,895), Belgium (42,677) and France (38,747). In terms of overall population, Belgium (4.2 applicants per 1,000 inhabitants), Ireland (2.9), the Netherlands (2.8) and Austria (2.3) had the highest rates of asylum requests. October 1999 called for the development of a common EU policy in these areas including the following elements: partnership with countries of origin, a common European asylum system, fair treatment of third country nationals and management of migration flows. A detailed programme of action is set out in the "Scoreboard to review progress on the creation of an area of freedom, security and justice in the European Union"(Biannual update COM (2002) 261). The Commission has already put forward proposals for the establishment of a common asylum procedure and a uniform status (COM(2000)755 final and COM(2001)710 final) and for a Community immigration policy (COM(2000)757 and COM(2001)387) together with a Areas of social policy concern - Statistical portraits Section 3 number of Directives which will be followed by others setting out the necessary legal framework. Some countries include some dependents in their figures for asylum applications, other countries do not. The same applies to repeat applications. The details are given in the table “Asylum applications” in the part “2 POPULATION” in Annex II. Furthermore, following the Treaty of Amsterdam, asylum and migration are transferred from the intergovernmental third pillar to the community first pillar, with decisions in these fields being shaped in Community instruments such as directives. Links to other parts of the report Methodological notes Demography, households and families (3.2), Population (Annexes II and IV) Source: Eurostat - Migration Statistics. Further reading Population growth rates represent the relative increase of the total population per 1,000 inhabitants during the year(s) in question. The increase in total population is made up of the natural increase (live births less deaths) and net migration. Net migration is estimated on the basis of the difference between population change and natural increase (corrected net migration rate per 1,000 inhabitants). ● Total immigration flows include immigration of nationals and non-nationals. Different Member States apply different definitions of migration. Often, statistics are based on a person registering as a resident in another country or on a stated intention to stay longer than a certain period in a country (typically twelve months or more). ● ● ● ● ● “European social statistics - Migration”, 2002 edition. Eurostat. “European social statistics - Demography”, 2002 edition. Eurostat. Statistics in Focus (Population and social conditions): “First results of the demographic data collection for 2001 in Europe”, No.17/2002. Eurostat. “Patterns and trends in international migration in Western Europe”, 2000. Eurostat. “Migrants’ insertion in the informal economy, deviant behaviour and the impact of receiving societies”, European Commission DG Research report 2000. “The social situation in the European Union 2002”, pages 16-51, 2002. European Commission, DG for Employment and Social Affairs and Eurostat. Key indicator EU-15 B DK D EL E F IRL I L NL A P FIN S UK 3.1 3.1 3.2 1.3 2.3 1.9 3.2 2.0 3.3 1.2 5.8 8.8 1.0 0.8 7.8 7.0 2.9 3.1 7.5 8.3 3.1 3.6 2.2 2.1 6.3 4.9 1.2 0.5 3.2 2.7 2.6 3.3 1.9 2.8 1.1 1.9 3.0 2.0 2.5 7.0 1.9 5.7 1.1 0.4 0.7 1.3 4.3 -0.4 2.1 1.9 10.0 10.5 2.0 2.7 1.0 7.5 1.1 -1.3 0.8 1.8 1.1 3.7 2.0 1.3 Net migration rate (per 1 000 population) 2001 2000 Average annual net migration rate 1995-99 1990-94 Source: Eurostat - Demographic Statistics Average annual rate of population change by component, EU-15, 1960-2001 Graph 8 per 1000 population 8 Natural increase Net migration 9 700 8 600 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 -1 800 800 10 10 9 Asylum applications, EU-15, 1985-2000 1960-64 1965-69 1970-74 1975-79 1980-84 1985-89 1990-94 1995-99 2000 2001 Source: Eurostat - Demographic Statistics 600 500 400 400 300 300 200 200 100 100 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Source: Eurostat - Migration Statistics 121 700 500 0 -1 Thousands Graph 7 0 Section 3 Areas of social policy concern - Statistical portraits 5 Education and its outcomes Attainment levels of the population have improved significantly over the last thirty years, particularly among women. Today 75% of young people aged 25-29 in the Union have an upper secondary qualification. At the same time, however, 19% of people aged 18-24 leave the education system with only lower secondary education at best. Younger generation is better qualified By comparing those currently leaving the education system with older generations, it is possible to monitor the trends in educational attainment over a long time-period of around thirty years. In 2001, 75% of the younger generation aged 25-29 had completed at least upper secondary education (GCE 'A' levels, Baccalauréat, Abitur, apprenticeship or equivalent) compared with only 52% of people aged 50-64. In general, attainment levels are higher in the northern Member States: between 80% and 91% of young people aged 25-29 in the three Nordic countries, Germany, Austria and France have an upper secondary qualification. Ireland, Spain, Italy, Luxembourg and Portugal record the lowest levels of educational attainment (below 70%) but have, apart from Luxembourg, witnessed the most significant increases in the last three decades. In these countries, the proportion of the youngest generation having completed at least upper secondary education is more than twice that of the oldest generation. Greece has also more than twice as many of the young generation as of the oldest with this qualification. As a result, the gap in attainment levels between the Member States is narrowing. To put the above figures into context, it is useful to look at the activity status of 18-24 year-olds. EU-wide, a little more than half of this age-group are in education/training (16% combine their studies with a job) and it can be assumed that the majority have already attained at least an upper secondary qualification. The picture across the Union is far from homogeneous due to differences in the education systems, length of study, labour market situation, opportunities for young people without work experience, etc. See also Youth unemployment (3.10). Higher qualifications tend to reduce the risk of unemployment… In general, higher education qualifications seem to reduce, albeit to differing degrees, the chances of unemployment in all Member States. In EU-15, the unemployment rate of people with a tertiary education qualification stood at 4% in 2001 compared with 6% for people who had completed at best upper secondary education and 9% among those who had not gone beyond lower secondary schooling. …and increase income… Over the last thirty years or so, disparities in attainment levels between the sexes have been reduced throughout the Union (in the younger generation women have even slightly overtaken men). For example, while 77% of young EU women aged 25-29 have an upper secondary qualification compared with 74% of men, only 46% of women among the population aged 50-64 have such a qualification compared with 58% of men of the same age. See Annex II for data per Member State. Data show also that a person's income is likely to be considerably higher if he/she is better qualified. On average, the equivalised income of a person with less than upper secondary education was 90% of the national median compared with 147% for those with tertiary education. This discrepancy between the low and best qualified was largest in Ireland (82% v 185%) and Portugal (92% v 287%) and smallest in Denmark (88% v 117%) and Germany (95% v 124%). Almost one in five 'school leavers' are low-qualified Data also show that the likelihood of a member of a high-level educated household (i.e. at least one member had completed tertiary education) to live persistently in a low-income household was only 3% compared with 12% among those from a low-level educated household (i.e. all members had completed at most lower-secondary schooling). Although educational attainment levels continue to improve, 19% of 18-24 year-olds in the Union have left the education system without completing a qualification beyond lower secondary schooling (the equivalent of full-time compulsory schooling in all Member States). Italy (26%), Spain (29%) and Portugal (45%) have the highest proportions of low-qualified young people. In virtually all Member States, women (EU average of 17%) are less likely than men (EU average of 22%) to fall into this category. 122 …and lead to more training opportunities Throughout the Union, the higher the educational level of adults, the greater the training opportunities afforded to them. See also Lifelong learning (3.6). Areas of social policy concern - Statistical portraits Section 3 Policy context UNESCO 1997 version). Less than upper secondary corresponds to ISCED 0-2, upper secondary level to ISCED 34 (including thus post-secondary non-tertiary education) and tertiary education to ISCED 5-6. The full-time compulsory education in all Member States includes ISCED 2. In Belgium, Germany and the Netherlands there is a compulsory part-time ISCED 3 level education till the age of around 18 years. The key indicator shows the number of persons aged 18-24 who have left the education system with low qualifications as a proportion of the total number of persons aged 18-24. EC Treaty (Title XI, Chapter 3, Art.149(1): "The Community shall contribute to the development of quality education by encouraging co-operation between Member States and, if necessary, by supporting and supplementing their action …" and Art.150(1): "The Community shall implement a vocational training policy which shall support and supplement the action of the Member States …". In its Communication on the Future of the European Employment Strategy the Commission outlines the need to reduce school failure and drop outs and raising the quality of education as a priority area for the new EES. Such policies should lay the ground for future access to lifelong learning, and remain important challenges for many current and future Member States. In the 2001 Employment Guidelines Member States were called upon to improve the quality of their education and training systems as well as the relevant curricula in order to: equip young people with the basic skills relevant to the labour market and needed to participate in lifelong learning; reduce youth and adult illiteracy and substantially reduce the number of young people who drop out of the school system early (a common target has been set of halving by 2010 the number of early school leavers aged 18-24 years); promote conditions to facilitate better access for adults, including those with atypical contracts, to lifelong learning so as to increase the proportion of adult working age population (25-64 year olds) participating at any given time in education and training. In order to facilitate mobility and encourage lifelong learning, Member States should improve the recognition of qualifications, acquired knowledge and skills. Links to other parts of the report Lifelong learning (3.6), Employment (3.7), Employment of older workers (3.8), Unemployment (3.9), Youth unemployment (3.10), Education and training (Annexes II and IV). Further reading ● ● ● ● ● ● The European Commission White Paper “a new impetus for European Youth” (COM(2001) 681 final, 21.11.2001) “suggests giving the European Union a new framework for cooperation in youth policy. In doing so, it is responding to strong demand from all parties concerned with youth policy, including the Member States. This cooperation will draw on existing national and Community activities, but will also be based on arrangements for applying the open method of coordination in the specific field of youth, and for taking more account of youth in other policies.” ● ● ● ● Methodological notes Sources: Eurostat - European Union Labour Force Survey (LFS) and Structure of Earnings Statistics. The levels of education are defined according to ISCED (International Standard Classification of Education - 123 “Education across Europe - Statistics and indicators 1999”, 2000, Eurostat. “Key data on education in Europe – 2002", 2002, DG Education and Culture, Eurostat and Eurydice (Information network on education in Europe). “The transition from education to working life: Key data on vocational training in the European Union”, 2001, DG Education and Culture, Eurostat and Cedefop (European Centre for the development of Vocational Training). “Young People’s Training: Key data on vocational training in the European Union”, 1999, DG Education and Culture, Eurostat and Cedefop. “Employment in Europe 2001". European Commission, Employment and Social Affairs DG. “Education for the twenty-first century: issues and prospects”, 1998, UNESCO Publishing. “An age of learning: vocational training policy at European level”, 2000, Cedefop. “Education at a glance 2002”, 2002, OECD. “Education for All – An international strategy to put the dakar Framework for Action on Education for All into operation”, 2002, UNESCO, http://www.unesco.org/education/efa/index.shtml. Statistics in Focus (Population and social conditions): "Persistent income poverty and social exclusion in the European Union", No.13/2000. “Educating young Europeans”, No. 14/2000. “Foreign language teaching in schools in Europe”, No. 4/2001. “Education in the regions of the European Union”, No. 6/2001. “Educational attainment levels in Europe in the 1990s – some key figures”, No. 7/2001. “Employment in the EU Regions 2000: Job creation is driven by the service sector – education is essential”, No. 13/2001. “Women and men in tertiary education”, No. 18/2001. Eurostat. Section 3 Areas of social policy concern - Statistical portraits Key indicator EU-15 B DK D EL E F IRL I L NL A P FIN S UK Early school-leavers not in further education or training (Share of the population aged 18-24 with less than upper secondary education (ISCED 0-2) and not in education or training) 19 2001 14 17 13 17 29 14 19 26 18 15 10 45 10 11 : 37 25 32 6 27 29 33 11 2 45 32 21 7 45 36 13 9 47 31 13 11 32 42 14 3 45 31 22 8 49 36 7 44 18 33 5 15 30 46 8 7 36 48 10 28 30 31 12 19 31 40 9 30 19 38 13 Population aged 18-24 by activity status (%), 2001 16 36 34 14 In education and employment In education and not in employment Not in education and in employment Not in education and not in employment 6 49 33 12 Notes: IRL 1997 data. UK - Data not shown for early school leavers. A definition of 'upper secondary attainment' has still to be agreed. Source: Eurostat - European Union Labour Force Survey Graph 9 100 Percentage of population that has completed at least upper secondary education, by age-group, 2001 86 80 75 77 75 Aged 25-29 Aged 50-64 84 80 78 76 89 87 91 62 80 69 67 67 56 52 38 40 30 20 10 D EL E 10 7 5 5 6 F IRL I L NL A P 5 4 3 20 10 DK 9 8 40 26 EU-15 B 11 32 31 20 15 10 50 45 30 15 60 56 50 50 Males Females All 70 61 60 20 % 90 78 69 70 0 20 100 % 90 50 Graph 10 Unemployment rates of the population aged 25-64 by sex and level of education, EU-15, 2001 5 10 FIN S UK 0 0 0 Less than upper secondary Source: Eurostat - European Union Labour Force Survey. IRL: 1997 data. UK - Data not shown. A definition of upper secondary attainment has still to be agreed. Upper secondary and postsecondary, not tertiary Tertiary Source: Eurostat - European Union Labour Force Survey Note: UK - GCSE ‘O’ levels are included under upper secondary (ISCED 3). 124 Areas of social policy concern - Statistical portraits Section 3 6 Lifelong learning EU-wide, 8% of the population aged 25-64 participated in education/training (in the last four weeks) in 2001. Such training activities seem to be more prevalent in the Nordic countries, the Netherlands and the United Kingdom. Older people are less likely to receive training than younger people. Higher qualified people are more likely than the low-qualified to participate in such training. Lifelong learning is more common in the Nordic countries, the Netherlands and United Kingdom was higher in medium-sized enterprises (50-249 employees) than in small enterprises (10-49 employees), and higher still in large enterprises, although in nearly all countries only the differences between small and medium-sized enterprises were significant. In spring 2001, 8% of the population aged 25-64 declared that they had received education or training during the four weeks preceding the interview. Levels of participation are highest (16-22%) in the Nordic countries, the Netherlands and the United Kingdom. All other Member States have percentages below or equal to the EU average. In France, the figure is also low but a different reference period is used (see methodological notes). Concerning participation of employees to CVT courses, most Northern EU Member States have a share over the EU average. The lower shares observed are in Portugal and in Greece with respectively 17% and 15%. Training intensity is not related to participation rate or to the percentage of enterprises providing continuing vocational training. Spain, Greece and Portugal have lower shares in training enterprises but higher number of hours in courses per participant. Participation of women varies considerably from country to country For the Union as a whole, slightly more women (9%) than men (8%) receive training. The gap in favour of women is particularly large in Denmark (19% v 16%), Finland (21% v 17%), Sweden (20% v 15%) and especially the United Kingdom (26% v 18%). In contrast, in Belgium, Greece, Germany, Luxembourg, the Netherlands and Austria, men are more likely to participate than women. Age of students in tertiary education varies considerably An alternative way of measuring "lifelong learning" is to look at the proportion of students in tertiary education (i.e. education which focuses on university or equivalent post-secondary education) who are aged 30 or over. In 1999/2000, around 1.3 million students in tertiary education in the Union were aged 30 or over. Put another way, this age group accounted for 12% of all students in tertiary education. In Denmark (22%), Germany (22%), Austria (25%), Finland (28%) and Sweden (22%) the proportion is considerably above the average. The young and the qualified participate more in education and training Throughout the Union, the level of participation in such training activities decreases with age: from 14% among those aged 25-34 to 3% among the 55-64 age-group. It is worth noting however that the proportion of people receiving training in the older age-groups remains relatively high in some countries: between 7% and 13% of 55-64 year-olds in Denmark, the Netherlands, Finland, Sweden and the United Kingdom. Public expenditure on education: 5.0% of EU GDP Although investment in education is influenced by various factors (e.g. demographical aspects or levels of participation and length of study), the percentage of national wealth devoted to education tends to reflect the importance which governments attach to it. Public resources allocated to the funding of all levels of education - not including private sources - represented on average 5.0% of the Union’s GDP in 1999. A government’s contribution to education may vary greatly from one country to another, ranging from 3.6% of GDP in Greece to 7.7% in Sweden and 8.1% in Denmark. The distribution of education budgets by level of education was more consistent, with primary and higher education each accounting for 1.1% on average of GDP, while secondary education accounts for 2.3%. The level of education attained also influences the chances of participation in "lifelong learning" for people aged 25-64: in 2001, 15% of those with a tertiary qualification received training, compared to 2% of those with the lowest level of education. Northern and central EU Member States: higher share of training enterprises The proportion of all enterprises in the EU Member States that provided training in 1999 ranged from 18% in Greece to 96% in Denmark. The percentage of enterprises providing continuing vocational training (CVT) 125 Section 3 Areas of social policy concern - Statistical portraits Policy context EC Treaty (Title XI, Chapter 3, Art.150(2): "Community action shall aim to … facilitate access to vocational training …; stimulate co-operation on training between educational or training establishments and firms; In it's Communication on the Future of the European Employment Strategy the Commission outlines the key link played by lifelong learning in improving quality at work and productivity, and as a factor promoting labour force participation and social inclusion. In particular the growing inequality in access to training, to the disadvantage of less skilled and older workers, is a priority. The current trend whereby firms' investment in training declines with the age of workers should be reversed. The 2001 Employment Guidelines included for the first time a horizontal guideline asking for "comprehensive and coherent national strategies for lifelong learning" in order to promote employability, adaptability and participation in the knowledge-based society. Member States were also invited to set, and monitor progress towards, targets for increasing investment in human resources and participation in further education and training. The Lisbon European Council in March 2000 identified four key areas as part of an active employment policy. One of these areas was "giving higher priority to lifelong learning as a basic component of the European social model, including by encouraging agreements between the social partners on innovation and lifelong learning; by exploiting the complementary link between lifelong learning and adaptability through flexible management of working time and job rotation; and by introducing a European award for particularly progressive firms. Progress towards these goals should be benchmarked; ". The Lisbon Conclusions call for increased investment in human resources. Social Policy Agenda (COM(2000) 379 final), Section 4.1.1.1 stresses the need to focus "efforts on improving people's employability and reducing skill gaps, in particular through developing life-long learning, e-learning and scientific and technological education; developing and improving education and training systems so as to implement a strategy for the 'lifelong education of all'." A Communication on "Making a European Area of Lifelong Learning a Reality" (COM(2001) 678 final of 21.11.2001) adopted by the Commission sets out proposals for improving the participation of Europeans in lifelong learning activities. In this communication lifelong learning is defined as “all learning activity undertaken throughout life, with the aim of improving knowledge, skills and competences within a personal, civic, social and/or employment-related perspective”. A Report from the Education Council to the European Council on "The concrete future objectives of education and training systems" was presented in Stockholm in 2001. In this the Ministers of Education adopted the following concrete strategic objec2 tives: increasing the quality and effectiveness of education and training systems in the European Union; facilitating the access of all to the education and training systems; opening up education and training systems to the wider world. These common objectives provide a basis for Member States to work together at European level over the next ten years, following the “Detailed work programme on the follow-up of the objectives of Education and training systems in Europe” (Official Journal of the European Communities 2002/C 142/1), to contribute to the achievement of the goals set out by Lisbon, especially in the context of the Luxembourg and Cardiff processes. The Working group G (open learning environment, active citizenship, social inclusion) for the Educational Objectives Report has the special task to develop policy objectives until 2010 in this field. The Commission Communication “Investing efficiently in education and training: an imperative for Europe” (COM 2002 779 final, 0.01.2002) sets out the Commission's view on the new investment paradigm in education and training in the enlarged EU within the framework of the ambitious strategic goal set by the Lisbon European Council in March 2000. In view of this goal, Ministers in charge of education adopted in February 2002 the “Detailed work programme on the objectives of education and training systems”, including its objective 1.5: “Making the most efficient use of resources”. The Education/Youth Council of 30 May 2002 adopted a resolution on education and lifelong learning (Official Journal C 163 of 9 July 2002), reaffirming the need for a convergence of the Commission's Communication entitled Making a European area of lifelong learning a reality with the work programme on the follow-up of the objectives of the education and training systems, in order to achieve a comprehensive and coherent strategy for education and training. On 30 November 2002 the education Ministers of 31 European countries and the European Commission adopted the Copenhagen Declaration on enhanced cooperation in European vocational education and training (http://europa.eu.int/comm/education/copenhagen/index _en.html). Communication on Investment in Education (COM 2002 779 of 10.01.2003) Methodological notes Sources: Eurostat - European Union Labour Force Survey (LFS) and UOE (UNESCO, OECD and Eurostat) questionnaires on education statistics (for public expenditure data). Although some statistical information has been presented above on "lifelong learning" (LLL), the notion of LLL is vast and to study it requires a clear identification of the themes that need to be explored as a priority. Moreover, some aspects are simply not measurable. Statistical information must therefore be complemented by contextual information. A Task Force that was set up by Eurostat to look at, among other things, the priorities for LLL and discuss their operationalisation in terms of statistical needs has produced its final report in February 20012. This report underlines the need of going at the level of the individual http://forum.europa.eu.int/Public/irc/dsis/edtcs/library?l=/public/measuring_lifelong 126 Areas of social policy concern - Statistical portraits Section 3 to improve our knowledge base on lifelong learning and proposes an EU Adult Education Survey (AES) for 2006. The discussions on this survey are currently held in the framework of the Task Force on the AES, which is expected to complete its work by the end of 2003. In parallel an ad hoc module on lifelong learning will be included in the EU LFS in 2003. ● ● ● For most Member States, data refer to persons who had received education or training during the four weeks preceding the interview. In France training must occur at the time of the interview for it to be counted. ● ● The second survey of continuing vocational training (CVTS2) was carried out by the European Commission in 2000/2001 in all the Member States, Norway and nine Candidate Countries. ● ● Expenditure on education for 2000 and 2001 are preliminary data. ● Links to other parts of the report Education and its outcomes (3.5), Employment (3.7), Employment of older workers (3.8), Unemployment (3.9), Education and training (Annexes II and IV) Further reading ● ● “Education across Europe - Statistics and indicators 1999”, 2000, Eurostat. “Key data on education in Europe – 2002", 2002, DG Education and Culture, Eurostat and Eurydice (Information network on education in Europe). ● Key indicator EU-15 B DK D EL E F Lifelong learning (Percentage of population aged 25-64, participating in education and training in the 4 weeks prior to the survey), 2001 8 14 8 6 3 Total, 25-64 25-34 35-44 45-54 55-64 7 12 8 5 2 18 27 19 14 8 5 13 5 3 1 1 4 1 0 0 5 11 3 2 1 3 6 2 1 0 "European Social Statistics - Continuing Vocational Training Survey (CVTS2)", Eurostat, 2003. “The transition from education to working life: Key data on vocational training in the European Union”, 2001, DG Education and Culture, Eurostat and Cedefop (European Centre for the development of Vocational Training). “Young People’s Training: Key data on vocational training in the European Union”, 1999, DG Education and Culture, Eurostat and Cedefop. “Education for the twenty-first century: issues and prospects”, 1998, UNESCO Publishing. “An age of learning: vocational training policy at European level”, 2000, Cedefop. "Education at a glance 2002", 2002, OECD. Statistics in Focus (Population and social conditions): “Public expenditure on education in the EU in 1997”, No.8/2000, Eurostat Statistics in focus on CVTS2 (Population and social conditions), Eurostat. - First survey on continuing vocational training in enterprises in candidate countries (2/2002) - Continuing vocational training in enterprises in the European Union and Norway (3/2002) - Costs and funding of continuing vocational training in enterprises in Europe (8/2002) - Providers and fields of continuing vocational training in enterprises in Europe (10/2002) - Disparities in access to continuing vocational training in enterprises in Europe (22/2002) - Working time spent on continuing vocational training in enterprises in Europe (1/2003) “Making a European Area of Lifelong Learning a Reality", COM(2001) 678 final of 21.11.2001. IRL I L NL A P FIN S UK 5 9 5 3 1 5 12 3 2 1 5 9 6 3 1 16 25 18 13 7 8 14 8 7 2 3 8 2 1 0 19 28 21 18 8 17 25 18 15 10 22 26 24 20 13 Notes: F - training must occur at the time of the interview for it to be counted. IRL: 1997 Data. Source: Eurostat - European Union Labour Force Survey Graph 12 Spending on human resources (Total public expenditure on education as a percentage of GDP), 1999 and 2000 Graph 11 Lifelong learning (Percentage of population aged 25-64, participating in education and training in the 4 weeks prior to the survey) by level of education, EU-15, 2001 9 9 1999 2000 8 20 20 % 15 15 10 10 15 10 5 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 5 2 0 0 Lower secondary or less Upper secondary and postsecondary, not tertiary Tertiary 0 Notes: F - training must occur at the time of the interview for it to be counted IRL 1997 data. UK - GCSE 'O' levels are included under upper secondary (ISCED 3). Source: Eurostat - European Union Labour Force Survey EU-15 B DK D EL E Source: Eurostat - Education Statistics 127 F IRL I L NL A P FIN S UK 0 Section 3 Areas of social policy concern - Statistical portraits 7 Employment In 2001, an estimated 168 million people were in employment in the Union, a rise of more than 12 million since 1996. This represents annual employment volume growth of around 1.5% per annum. In 2001, employment increased by 1.2%. The employment rate for the population aged 15-64 stood at 64% in 2001. Slow-down of the employment growth in the EU In 2001, almost 168 million people were in employment in the Union, a rise of 11.8 million since 1996. The largest increase in absolute terms in the number of people in employment was in Spain (+2.3 million) and France (+1.9 million). Compared with the year before, employment increased by 1.2% in the Union, a slow-down compared with the 1.8% growth between 1999 and 2000. Although in 2001, employment rose in all Member States except Greece, the growth was less than the previous year in all Member States. In Ireland, Spain, the Netherlands and France, employment growth was still 2% or more but in Denmark, Germany and Austria, employment growth was only 0.2%. The United Kingdom (0.8%) also had an employment growth below the EU average. Over the period (1996-2001) the services sector accounted for almost the entire net employment growth. In contrast, employment decreased by more than half a million in the agricultural sector in all Member States. EU employment rate still lagging behind US and Japan In 2001, the employment rate for the population aged 15-64 ranged from 55% in Italy and Greece to 76% in Denmark. Denmark, the Netherlands, Austria, Portugal, Finland, Sweden and United Kingdom have already reached the EU overall employment rate target of 67% for 2005 (see below under "policy context"). The EU average of 64% is considerably less than in the case of the US (73%) and Japan (69%). The gender gap in employment rates in the Union is 18.1 points (73% for men compared with 54.9% for women). See Female employment (3.18). 69% of total employment in the services sector EU-wide, 4% are employed in agriculture, hunting, forestry and fishing, 26% in industry and the remaining 69% in services. This pattern is rather similar throughout the Member States with the exception of Greece and Portugal, which still have a relatively large share of people working in agriculture, hunting, forestry and fishing, respectively 16% and 11%. The latter may explain, in part, the rather high proportion of self-employed people in these two countries: 43% and 28% respectively compared with an average of 15% for the Union as a whole. However, in general, Greece has amongst the highest rates of self-employment in all sectors. Italy is the third Member State with a relatively high self- 128 employment rate (26%), particularly in the services. There are differences between genders, as 84% of the women in employment are working in the services sector but only 14% in the industry. At sub-national level, regions hosting Member State capitals tend to have the highest proportion of people employed in the service sector: in 2001, Inner London (89% of total employed) in the United Kingdom, Brussels-capital (84%) in Belgium, Stockholm (84%) in Sweden, Île de France (81%) in France, Lazio (78%) in Italy, Berlin (79%) but also Hamburg (78%) in Germany, Vienna (78%) in Austria, Uusimaa (78%), the larger area around Helsinki in Finland and Attiki (74%) in Greece. In Spain and Portugal, two regions outside the capital have the highest proportion of people employed in the service sector (Ceuta & Melilla, 85% and Algarve, 70%) Part-time work continues to rise Part-time employment, a reduction and sometimes a polarisation of working hours - when employed people move away from the standard working week into both short and long hours - and fixed-term contracts are now common structural characteristics of employment in the EU. The share of part-time employment has increased from 14% of all employment in 1991 to 18% in 2001. More than 20% of people in employment in Denmark, Germany, Sweden and the United Kingdom and over 40% in the Netherlands is working part-time. However, Greece, Spain and Italy are exceptions where part-time employment is 8% or less. The largest part of part time workers are women. The proportion of EU employees with a fixed-term contract has remained stable in the past three years (13%). Spain has by far the highest proportion (32%). EU-wide, 61% of fixed-term contracts are for a period of less than one year. Full-time employees work for an average of 40 hours per week In 2001, full-time employees in EU-15 worked for an average of 40 hours per week. The picture was relatively homogeneous throughout the Union with the exception of the United Kingdom (44 hours). EU-wide, almost 19% of full-time employees were working longer than the average of 40 hours per week. Around 8% usually worked at least 49 hours per week. The figure for the United Kingdom was as high as 21%. In the Union, a large proportion of these employees working long hours (40%) are legislators, senior officials, managers Areas of social policy concern - Statistical portraits Section 3 and professionals. In Spain, Greece and Portugal however, most are services and sales workers. Men work more hours than women in all Member States although in Austria and Sweden the difference was less than one hour. In contrast, the gender gap was more than 4 hours in the United Kingdom. At EU level, 15% of employees had jobs that require them usually or sometimes to work at night, while 23% worked on Sundays in 2001. Combining this data (along with Saturday work), 49% of male employees and 42% of women were working at other times than during day time hours on weekdays. Policy context Methodological notes The Amsterdam European Council (June 1997) introduced new employment provisions in the Treaty. Whereas, according to art. 127, Community policies should pursue a high level of employment, employment was declared in art. 126 a matter of common concern for the Member States. The new Art. 128 instituted an open coordination method for developing national employment policies on the basis of shared European priorities, reflected in the European Employment Guidelines. The Guidelines have to be taken into account in national action plans (NAPs), which are assessed through the Joint Employment Report from the Commission and the Council, with a view to set the next annual guidelines. Since 2000, the Guidelines are complemented by specific recommendations to Member States. To strengthen the monitoring process, the Guidelines may set targets at EU or national level. Sources: Eurostat quarterly labour force data (QLFD) are based on the EU Labour Force Survey (LFS) and on the European System of National Accounts (ESA 95). All other data come from the EU Labour Force Survey (LFS) in spring. Employment rates represent persons in employment aged 15-64 as a percentage of the population of the same age. Persons in employment are those who during the reference week (of the Labour Force Survey) did any work for pay or profit, including unpaid family workers, for at least one hour or were not working but had jobs or a business from which they were temporarily absent. The classification by part-time or full-time job depends on a direct question in the LFS, except for Austria and the Netherlands where it depends on a threshold on the basis of the number of hours usually worked. The first Guidelines were agreed at the Luxembourg "Jobs" Summit (November 1997) and articulated in the four integrated pillars of employability, entrepreneurship, adaptability, and equal opportunities. Later, the Lisbon European Council (March 2000) set full employment as an overarching long-term goal for the new European economy in the form of targets for employment rates for 2010 (70% overall and 60% for women). Subsequent adaptations to the Employment Guidelines were mainly triggered by the Stockholm Summit conclusions3 and the Nice European Council of December 2000, which introduced the issue of quality as a leading priority. Following the evaluation of the first five years of the EES and the request of the Barcelona European Council in March 2002 for a reinforced Employment Strategy, an entirely new set of Guidelines will be proposed by the Commission in the spring of 2003. The initial proposals of the Commission are outlined within the Communication on the Future of the European Employment Strategy published on the 14th January 2003. The Communication proposes that raising employment levels should become one of the overarching priorities for the Employment Guidelines, and that the Lisbon and Stockholm targets continue to play a central role in the guidelines. 3 Links to other parts of the report Education outcomes (3.5), Lifelong learning (3.6), Employment of older workers (3.8), Unemployment (3.9-10-11), Employment of women and men (3.19), Labour market policy expenditure Further reading ● ● ● ● ● “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. “European social statistics - Labour force survey results 2000”, 2001. Eurostat. Taking stock of five years of the EES, COM(2002)416 final of 17 July 2002 Statistics in Focus (Population and social conditions):"Labour Force Survey Principal Results 2000", No.10/2001. Eurostat. Statistics in Focus (Population and social conditions):"Employment in the EU Regions 2000: Job creation is driven by the service sector – education is essential”, No. 13/2001. Eurostat. The Stockholm European Council complemented the Lisbon targets with intermediate targets for the employment rate to be reached in 2005: 67% overall and 57% for women. In addition, a new employment rate target of 50% was set for older persons (for 2010). 129 Section 3 Areas of social policy concern - Statistical portraits ● ● Statistics in Focus (Population and social conditions):"Employment rates in Europe – 2000”, No 8/2001. Eurostat. “Industrial Relations in Europe", 2000. European Commission, Employment and Social Affairs DG. Key indicator ● “Employment precarity, unemployment and social exclusion" and "Inclusion through participation", European Commission DG Research reports 2000. EU-15 B DK D EL E F IRL I L NL A P FIN S UK 64.0 63.2 59.3 60.5 76.2 76.3 65.8 65.4 55.4 55.7 56.3 54.8 63.1 62.0 65.7 65.2 54.8 53.7 62.9 62.7 74.1 72.9 68.4 68.4 68.8 68.3 68.1 67.3 71.7 70.8 71.7 71.5 167.9 Total employment 2001 (millions) 165.8 Total employment 2000 (millions) 156.1 Total employment 1996 (millions) 2001/1996 (% aver. annual empl. growth) 1.5 1.2 2001/2000 (% annual empl. growth) 4.0 3.9 3.7 1.2 1.2 2.8 2.8 2.6 1.1 0.2 38.8 38.7 37.3 0.8 0.2 3.9 3.9 3.8 0.7 0.2 16.0 15.6 13.7 3.1 2.5 24.8 24.3 22.8 1.7 2.0 1.7 1.7 1.3 5.5 2.9 23.5 23.1 22.1 1.2 1.6 0.3 0.3 0.2 2.1 2.2 8.3 8.1 7.3 2.6 2.1 4.0 4.0 3.9 0.6 0.2 5.0 4.9 4.5 1.9 1.6 2.3 2.3 2.1 2.2 1.2 4.3 4.2 4.1 1.2 1.9 28.2 27.9 26.5 1.2 0.9 Employment rate, 15-64 years 2001 2000 Trend in employment Source: Eurostat - Quarterly Labour Force Data (QLFD). Graph 13 Employment rates (15-64 years), 2001 100 Graph 14 Average annual employment growth, 1996-2001 100 % 80 76,2 74,1 71,7 71,7 6 68,4 68,1 65,8 65,7 64,0 63,1 62,9 60 59,3 6 5,5 5 5 80 68,8 % 4 4 56,3 55,4 54,8 60 3,1 3 40 20 NL UK S P A FIN D IRL EU-15 F L B E EL 2 1,2 1,2 1,1 1 0 DK 1,9 1,7 1,5 1,2 0 2,2 2,1 2 20 3 2,6 40 0,8 0,7 D EL 1,2 1 0,6 0 0 EU-15 B I Source: Eurostat - Quarterly Labour Force Data (QLFD). DK E F IRL I L Source: Eurostat - National Accounts (ESA 95) 130 NL A P FIN S UK Areas of social policy concern - Statistical portraits Section 3 8 Employment of older workers Although in the past four years, the EU employment rate of 5564 year-old men rose by 1.5 percentage points to stand at 48.7% in 2001, it is still below the 1991 rate (51.2%). In contrast, the comparable female rate increased steadily to reach 29% in 2001. Overall, 38.6% of the population aged 55-64 were in employment in 2001. In 2001, men exited the labour force on average at the age of 60.5 while women did so about 1.5 year earlier. The overall exit age was 60 years. Impact of population ageing on employment Employment rates remain high in Portugal beyond the age of 65 Population ageing will have a major impact on the labour market with the arrival of the first baby-boomer at the age of retirement. For the Union as a whole and in most Member States, the working age population (15-64 years) will stop increasing by 2010. This demographic decline will last several decades. Virtually all Member States will be affected although the intensity and timing of the trend vary at both national and regional levels. For example, in Germany, Greece and Italy, the decline has already begun. In contrast, the workingage populations of Ireland and Portugal are expected to peak in 2033 and 2023 respectively. No decline is expected in Luxembourg. Looking at more detailed age groups: the employment rate of the population aged 55-59 stands at 52.9% while it is 23.4% among those aged 60-64. Beyond the age of 65, the employment rate decreases sharply. EU-wide, less than 7% of those aged 65-69 are in employment. Portugal stands out with 28% of this age group in work. Exit from the labour force on average at the age of 59.9 years Preliminary calculations show that the average exit age from the labour force for the EU was 59.9 years in 2001. This exit age mirrors the trend of the activity rate (in the labour market) of older workers. Whereas in some Member States (Ireland, Portugal, Sweden and the United Kingdom) the average exit age is 62 or 63 years, none is close to 65 years. Men exit the labour force on average at the age of 60.5 while women do so about 1.5 year earlier. The effect on the labour supply and the economy of a decline in the working age population could be offset if, among other things, the employment rate were to increase among those of working age, including older workers. 16.7 million people in employment in the EU are aged 55-64 Higher proportion of older people working parttime EU-wide, 38.6% of the population around the retirement age (55-64 years) were in employment in 2001. The increasing rate in the past four years yielded a higher rate compared with 1991 (38.6% and 37% respectively). However, there are significant differences between the male and female rates over this period. The male rate for this age group fell until 1995 and has increased only since 1998. The female employment rate increased steadily (five points). Despite this trend, the rate for men (48.7%) remains considerably higher than that of women (28.9%). Among the people aged 55-64 in employment, 21.8% are working part-time in the Union as a whole. This is slightly higher than the proportion of part-timers aged 15-64 (18%). The largest gap between the generations is in Portugal (21.5% versus 6%). As with younger workers, women (42%) have a greater tendency than men (9%) to work part-time. Older workers are less likely than younger ones to receive training Sweden has by far the highest employment rate among older workers (66.5%) while the proportion in Denmark, Portugal and the United Kingdom is above 50%. At the other end of the scale, less than 30% of older people are working in Belgium, Italy, Luxembourg and Austria. Throughout the Union, training for employees decreases with age: EU-wide, from 10% of the 30-39 age group to 7% among 50-59 year-olds. The generation gap is smallest in Denmark, the Netherlands, Finland and the United Kingdom - countries with the highest overall levels of participation. Between 11-20% of employees aged 50-59 in these countries participated in training (in the four weeks before the interview) in 2001. 131 Section 3 Areas of social policy concern - Statistical portraits Policy context Achieving the Stockholm target of employment rate 50% for older workers and the Barcelona target on raising progressively the effective average exit age by about 5 years in 2010, requires determined efforts by Member States towards meeting the ageing related objectives of the European Employment Strategy. Policy orientations for older workers have been strengthened in the employment strategy since they were first introduced in guidelines 2000. Member States are devoting more resources to active ageing policies and there is now wider recognition that such policies are essential for our ability to face the challenges of ageing. The longer-term thinking reflected in the Lisbon and Stockholm targets led to greater awareness of the ageing and shrinking of the workforce and the need to shift the emphasis from piecemeal policies to comprehensive active ageing strategies as provided by the Joint Report4. This report pointed to the potential benefits of using a life cycle approach to raise and maintain higher participation and employment rates. Such strategies should reflect a dynamic preventative approach structured around a number of major objectives including the creation of more jobs and better quality in work, making work pay, promoting opportunities for skills upgrading and making work a real option for all. In the context of the comprehensive strategy, to be implemented through partnerships, priority is given to policy initiatives such as, promoting a joint Government/Social partners initiative to retain workers longer in employment; targeted review of tax/benefit systems; a more comprehensive, across the board approach to tackling gender gaps in pay and labour market access; providing better support for persons with care responsibilities; reviewing efforts to effectively reduce school drop-outs. The Communication on the Future of the EES proposes that the promotion of active ageing becomes a key element of the EES. View: Safe and Sustainable Pensions". Section 2.3 addresses the link between pensions sustainability, the Lisbon strategy and employment promotion: "Current pension systems tend to encourage early exit from the labour market and are frequently used to reduce staff levels while avoiding redundancies. They often do not take into account different individual needs. Some pension schemes offer insufficient coverage for the most mobile and flexible members of the workforce. More generally, the incentive structure of pension schemes needs to be reviewed to ensure that they become employment-friendly." Methodological notes Source: Eurostat - Quarterly labour force data and European Union Labour Force Survey (LFS). For definitions of activity rates (in the labour market) and employment rates, see Employment (3.7). Links to other parts of the report Ageing of the population (3.3), Lifelong learning (3.6), Employment (3.7), Unemployment (3.9), Labour market (Annexes II and IV) Further reading ● ● ● ● ● Moreover, the Commission adopted on 11 October 2000 a Communication (COM 2000-622 final) on the "Future Evolution of Social Protection from a Long-term Point of 4 “European social statistics - Labour force survey results 2000”. Eurostat. “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. “Combating Age Barriers in Employment: a European portfolio of good practice", 1998. European Foundation for the Improvement of Living and Working Conditions. “Employment precarity, unemployment and social exclusion" and "Inclusion through participation", European Commission DG Research reports 2000. "Increasing labour force participation and promoting active ageing" Council doc No 6707 0f 8 March 2002, adopted on the basis of COM(2002) 9 final of 24.01.2002. "Increasing labour force participation and promoting active ageing" Council doc. N° 6707 of 8 March 2002, adopted on the basis of COM(2002) 9 final of 24.01.2002 132 Areas of social policy concern - Statistical portraits Section 3 Key indicator EU-15 B DK D EL E F IRL I L NL Employment rate of older workers (employed person aged 55-64 as a share of the total population of the same age group), 2001 38.6 48.7 28.9 Total Men Women 26.5 36.5 16.9 58.0 65.5 49.8 37.7 46.1 29.5 38.0 55.0 22.5 38.9 57.4 21.8 31.0 35.4 26.7 46.8 64.7 28.8 28.0 40.4 16.2 24.4 34.8 14.0 A P FIN S UK 39.6 51.1 28.0 28.6 40.0 17.9 50.3 61.6 40.6 45.7 46.7 44.8 66.5 69.1 63.8 52.3 61.7 43.1 Effective average exit age (average exit age, weighted by the probability of withdrawal from the labour market), 2001 Total Men Women Persons in employment aged 55-64, 2001 (1000) 59.9 60.5 59.1 57.0 57.8 55.9 61.9 62.2 61.1 60.7 60.9 60.4 59.6 61.2 57.7 60.6 60.7 60.2 58.1 58.2 58.0 63.1 63.2 62.2 59.4 59.6 59.2 56.8 57.5 55.3 60.9 61.1 60.3 59.6 60.0 58.6 62.0 62.0 61.5 61.6 61.6 61.4 62.0 62.1 61.9 62.1 63.1 61.0 16662 259 352 4398 489 1578 1754 158 2002 16 654 270 542 254 695 3240 Source: Eurostat - European Union Labour Force Survey (LFS) and Quarterly Labour Force Data (QLFD) Graph 15 Employment rates by age-group and sex, EU-15, 2001 90 % 83,4 Male Female 80 70 60 Graph 16 Employment rates of older (aged 55-64) workers, 2001 70 80 60 60 50 50 40 40 30 30 20 20 10 10 70 64,2 59,3 % 90 70 60 50 50 41,9 40 40 31,8 30 30 20 20 15,5 9,3 10 4,3 4,5 10 1,9 0 0 0 50-54 55-59 60-64 65-69 S DK UK P IRL FIN NL E EU-15 EL D F A I 70-74 Source: Eurostat - European Union Labour Force Survey (LFS) Source: Eurostat - Quarterly Labour Force Data (QLFD) 133 B L 0 Section 3 Areas of social policy concern - Statistical portraits 9 Unemployment In 2001, the total number of unemployed in the European Union dropped to 12.8 million. This represents 7.4% of the labour force. This is the lowest rate since 1992. Between 2000 and 2001, Spain, France, Finland and Sweden recorded the largest fall in their unemployment rate although Spain continues to have the highest figure (10.6%), slightly above Greece (10.5%). It decreased in all Member States, except in Portugal where it remained at a low 4.1%. EU unemployment continued to decrease In 2001, the total number of unemployed people in the EU stood at 12.8 million or 7.4% of the labour force. This is the lowest rate since 1992. The rate fell in all Member States except in Portugal, where it remained at a low 4.1%. The largest decreases were recorded by Italy, Spain, France, Finland and Sweden. Looking at the trend over a longer period - since the EU15 peak of 10.5% in 1994, rates in Denmark, Spain, Portugal, Finland and the United Kingdom fell by more than 40%. In Ireland and the Netherlands, the 2001 rates are just one third of the 1994 rates. In 2001, the countries with the highest unemployment continued to be Spain and Greece. In contrast, Denmark, Ireland, Luxembourg, the Netherlands, Austria, Portugal and Sweden recorded rates of less than 5%. These figures are similar to those for Japan (5.0%) and the United States (4.8%). Women are more likely than men to be unemployed in all but three Member States The female unemployment rate (8.7%) in the EU was still more than two points higher than the male unemployment rate (6.4%) in 2001, although the gap is on a declining trend. This less favourable situation for women was apparent in almost all Member States, especially in Greece, Spain and Italy, where the female unemployment rate was nearly twice the male one. The only exceptions were Ireland, Sweden and, in particular, the United Kingdom where 5.5% of active men (in the labour market) were unemployed compared to 4.4% of active women (in the labour market). Large regional disparities in unemployment National unemployment rates often mask important regional disparities within Member States, particularly in Germany (between west and east), Italy (between north and south) and the United Kingdom (also between north and south). In 2000 in Germany, the unemployment rate ranged from less than half the national average of 7.9% in Oberbayern (3.1%) to 16.9% in Dessau and Halle in Sachsen-Anhalt. Similarly, while many regions in the north of Italy were largely unaffected by unemployment, between 21-25% of the workforce in the southern regions of Campania, Calabria and Sicily was unemployed. In the United Kingdom, Merseyside in particular (13.2%) has a high unemployment compared with the South East (2.2%). Other regions in the Union where unemployment rates were considerably higher than the national average include Hainaut (13%) in Belgium, Andalucia and Extremadura (22%) in Spain, Languedoc-Roussillon (14%) in France (besides DOM) and Itä-Suomi (14%) in Finland. Regional disparities in unemployment are even more pronounced among young people (under 25 years of age). Dytiki Macedonia and Sterea Ellada in Greece and parts of Andalucia all recorded youth unemployment rates of 40% or more in 2001 and several regions in southern Italy even 50% or more. Policy context Methodological notes A key objective of the EES has always been to tackle high levels of unemployment across the EU. By embracing full employment as a key policy objective the strategy stresses a multi-dimensional approach to reducing unemployment, through active and preventative polcies, the provision of an adequate level of skills in order to compete in a modern labour force, and more intensive support for groupos facing particular disadvantage. Source: Eurostat - Unemployment rates and the European Union Labour Force Survey (LFS). 134 Unemployed people - according to the Commission Regulation n° 1897/2000 and International Labour Organisation (ILO) standards - are those persons aged 1574 who i) are without work, ii) are available to start work within the next two weeks and iii) have actively sought employment at some time during the previous four weeks or have found a job to start later, i.e. with a period of at most 3 months. Unemployment rates represent Areas of social policy concern - Statistical portraits Section 3 unemployed persons as a percentage of the active population (in the labour market) of the same age. The active population in the labour market (or labour force) is defined as the sum of employed and unemployed persons. Links to other parts of the report Education outcomes (3.5), Employment (3.7), Youth unemployment (3.10), Long-term unemployment (3.11), Labour Market Policy expenditure (3.14), Labour market (Annexes II and IV) Regional unemployment rates are based on the estimates of employed and unemployed persons taken from the Labour Force Survey at national level, in each case for a specific reference date in April. In a second step, the estimated jobless figures are broken down over the individual regions, applying the regional structures of registered unemployed persons or regionally representative results of labour force surveys. NUTS is the nomenclature of territorial units for statistics. The current nomenclature subdivides the territory of the Union into 78 NUTS 1 regions, 211 NUTS 2 regions and 1093 NUTS 3 regions. Though most NUTS 2-level regions are broadly comparable in size, there are some extreme variations. Further reading ● ● ● ● Key indicator EU-15 B DK D EL E F “European social statistics - Labour force survey results 2000”, Eurostat. “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. Statistics in Focus (Population and social conditions):"Labour Force Survey Principal Results 2000", No.10/2001. (General Statistics): "Unemployment in the regions of the European Union 1999", No. 3/2000. Eurostat. “Employment precarity, unemployment and social exclusion", European Commission DG Research report 2000. IRL I L NL A P FIN S UK Unemployment rate (total unemployed individuals as a share of total active population. Harmonised series) 2001 2001 2001 2000 1994 Total Men Women Total Total Unemployment, 2001 (1000) 7.4 6.4 8.5 7.8 10.5 6.6 6.0 7.4 6.9 9.8 4.3 3.8 4.9 4.4 7.7 7.7 7.7 7.8 7.8 8.2 10.5 7.0 15.6 11.1 8.9 10.6 7.5 15.4 11.3 19.8 8.6 7.0 10.3 9.3 11.8 3.8 3.9 3.7 4.2 14.3 9.4 7.3 12.9 10.4 11.0 2.0 1.7 2.4 2.3 3.2 2.4 1.9 3.0 2.8 6.8 3.6 3.0 4.3 3.7 3.8 4.1 3.2 5.1 4.1 6.9 9.1 8.6 9.7 9.8 16.6 4.9 5.2 4.5 5.8 9.4 5.0 5.5 4.4 5.4 9.4 12861 286 123 3073 457 1892 2221 68 2248 4 198 137 212 238 225 1485 Source: Eurostat - Unemployment rates (ILO definiton). Graph 17 Unemployment rates by sex, 2001 18 % Graph 18 Trend in the unemployment rate by sex, EU-15, 1993-2001 Male Female 16 18 13 16 12 14 14 12 12 10 8 8 6 6 4 4 2 2 10,5 11,1 Total 10,2 10 9,4 9 9,2 8,9 9,1 0 EU-15 B DK D EL E F IRL I L NL A P FIN S UK 11 10,2 10 10,1 9,4 9 12 11,6 11,7 11 10 11,7 11,9 11,5 10,1 13 Female % 8 Male 10 9,2 8,7 7,8 7,5 7 1993 Source: Eurostat - Unemployment rates (ILO definition). 7 6 1994 1995 1996 1997 1998 1999 Source: Eurostat - Unemployment rates (ILO definition). 135 8 7,3 6,7 6,4 6 0 9 8,5 8,2 2000 2001 Section 3 Areas of social policy concern - Statistical portraits 10 Youth unemployment EU-wide, 7.1% of young people (aged 15-24) were unemployed in 2001. The unemployment rate (as a percentage of the labour force) among young people was 14.7%. The differences between these two percentages vary significantly between countries, and may, in part be explained by the fact that a significant number of people in this age group remain in education. Youth unemployment/population ratio between 2000 and 2001 has not followed the overall, declining trend in unemployment: in five Member States it increased, in five remained the same, and in five decreased. Staying longer in education As the result of a longer stay in education, young people are now entering the labour market at a later age than in the past. For the Union as a whole, it is not until the age of 22 that at least 50% of young people are in employment for a minimum of twelve hours per week. However, there are considerable differences between Member States. For example, in Germany, Austria and the United Kingdom, the median age is 19 years. Youth unemployment is a result of the general labour market situation and also a reflection of how the educational and employment systems manage to complement one another with respect to the integration of the young in the labour market, and, in particular, of how well the education and training system prepares young people for the labour market. When looking at unemployment rates of 15-24 year-olds, it is important to bear in mind that the young people under consideration are largely first-time entrants onto the labour market and that a sizeable proportion have low qualifications. Around one in thirteen young people is unemployed In 2001, around 3.2 million young people aged 15-24 were unemployed in the Union. This represents 7.1% of the youth population or, put another way, 14.7% of the labour force of this age group. The youth unemployment rate ranges from less than 6% in the Netherlands and Austria to over 25% in Greece and Italy. Between 2000 and 2001, the number of young unemployed decreased by 5%, which is the same proportion as for the adult unemployed. As a result, the youth unemployment rate fell from 15.4% to 14.7%. However, the youth unemployment rate increased in Denmark, Ireland, Luxembourg, Austria and Portugal. Looking at the trend over a longer period - since the EU-15 peak of 20.9% in Policy context See previous portrait No 9. The 2002 Employment Guidelines particularly emphasised youth unemployment in Guideline 1, which states the need to "influence the trend in youth … unemployment. The Communication on the future of the EES calls for Member States to intensify their efforts to develop pre- 136 1994 - rates in nine Member States fell by at least a quarter. Spain, the Netherlands and Sweden saw their rates halved and Ireland recorded the largest drop of 70%. In five Member States the youth unemployment rate has not changed much. Germany (8-10%), Luxembourg (7%) and Austria (5-7%) have constantly had relatively low youth unemployment rates, whereas in Greece and Italy the rate has been about 30%. Young people are more than twice as likely as people aged 25 and over to be unemployed For the Union as a whole and in most Member States, people in the labour force who are less than 25 years of age are more than twice as likely as active people (in the labour market) aged 25 and over to be unemployed. In Belgium, Greece, Italy, Luxembourg, the Netherlands and the United Kingdom, the youth unemployment rate is more than three times the rate of those aged 25 and over. The large difference between the two rates reflects, in part, the fact that a significant number of people in this age group remain in education. The one exception is Germany where, in part due to the apprenticeship system, the rate for young people is only slightly higher than that for those aged 25 and over. Relatively more young unemployed women than men Young women in the labour force (15.7%) are more likely than young men (13.8%) to be unemployed. This is about the same gap as with the population aged 25 and over. The unemployment rate among young women is over 30% in Greece and Italy. In Germany and the United Kingdom, a significantly larger proportion of young men than young women are jobless. The long-term unemployment rate for people under the age of 25 stood at 6.9% in 2001. See Long-term unemployment (3.11). ventive and employability-oriented strategies and to reduce the levels of early school leavers. The Communication also suggests as a target the reduction in youth unemployment ratio to the levels of the best 3 performing Member States. See the “Policy context” part of the portrait No. 5 “Education and its outcomes”concerning the European Areas of social policy concern - Statistical portraits Section 3 Commission White Paper “a new impetus for European Youth” (COM(2001) 681 final, 21.11.2001). Further reading ● Methodological notes ● Source: Eurostat - Harmonised unemployment rates Unemployment is defined according to the ILO definition. See Unemployment (3.9) for definition. Youth unemployment population ratios show the unemployed aged 15-24 as a percentage of the population of the same age. Youth unemployment rates represent unemployed persons aged 15-24 as a percentage of the active population in the labour market (or labour force) of the same age. The active population (in the labour market) is defined as the sum of employed and unemployed persons. ● ● ● Links to other parts of the report “European social statistics - Labour force survey results 2000”, Eurostat. “Youth in the European Union. From Education to Working Life”, 1997. Eurostat. “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. Statistics in Focus (Population and social conditions):"From school to working life: Facts on youth unemployment", No.13/1998. Eurostat. “Youth unemployment and the processes of marginalisation on the northern European periphery", European Commission DG Research report 1999. "Employment precarity, unemployment and social exclusion", DG Research report 2000. Education outcomes (3.5), Employment (3.7), Unemployment (3.9), Long-term unemployment (3.11), Labour Market Policy expenditure (3.14), Labour market (Annexes II and IV) Key indicator B DK D EL E F IRL I L NL A P FIN S UK Youth unemployment/population ratio 7.3 5.8 2001 7.6 6.1 2000 10.4 8.2 1994 Source: Eurostat - Quarterly Labour Force Data (QLFD) EU 15 5.9 5.0 7.0 4.7 4.6 4.8 10.2 11.1 10.3 10.8 11.3 19.3 6.9 6.9 10.1 3.3 3.3 10.7 10.2 11.6 12.4 2.5 2.5 3.3 4.1 4.1 6.6 3.2 2.9 3.5 4.5 4.1 6.5 10.3 11.1 14.8 5.2 5.1 10.6 7.7 8.0 10.9 8.5 7.6 9.5 7.0 10.2 8.2 9.2 7.1 8.5 8.4 28.1 21.7 35.1 29.5 27.7 21.5 16.6 27.9 22.6 40.2 19.3 17.2 21.9 19.7 28.7 6.6 6.8 6.3 6.5 23.0 28.1 24.9 32.0 30.7 31.9 7.5 8.5 6.3 7.2 7.1 5.5 4.7 6.3 5.6 10.9 5.8 5.1 6.7 5.3 5.7 9.3 7.3 11.8 8.8 15.0 19.7 19.5 20.0 21.3 34.0 11.0 12.2 9.8 11.2 22.0 11.9 13.2 10.3 12.3 16.4 Youth unemployment rate 2001 total 2001 male 2001 female 2000 total 1994 total 14.7 13.8 15.7 15.4 20.9 17.6 16.5 19.1 17.0 23.2 Source: Eurostat - Unemployment Rates (ILO definition). Graph 19 Youth unemployment/population ratio (15-24 years), 2001 12 Graph 20 Youth unemployment rates (15-24 years) by sex, 2001 40 12 % 40 % Male Female 35 10 10 8 8 6 6 4 35 30 30 25 25 20 20 15 15 10 10 5 5 4 2 2 0 0 0 EU-15 B DK D EL E F IRL I L NL A P FIN S UK Source: Eurostat - Quarterly Labour Force Data (QLFD). EU-15 B DK D EL E F IRL I L NL A P FIN Source: Eurostat - Unemployment Rates (ILO definition). 137 S UK 0 Section 3 Areas of social policy concern - Statistical portraits 11 Long-term unemployment In 2001 3.3% of the EU-15 labour force were affected by longterm unemployment. Put another way, 44% of unemployed people were jobless for at least one year. The long-term unemployment rate has fallen in recent years but remains at 5% and over in Greece, Spain and Italy. For young people between 15 and 24 years old, 6.9% (as a percentage of the labour force) were unemployed for at least six months. Just under half the unemployed have been jobless for at least twelve months In 2001, 3.3% of the EU-15 labour force were unemployed for at least one year, a further decline of the long-term unemployment rate since 1997. In Denmark, the Netherlands, and Austria, less than 1% of the labour force was affected. In contrast, 5% of the active population (in the labour market) in Greece, Spain and Italy were unemployed for at least one year. Females more affected than men by long-term unemployment EU-wide, long-term unemployment is slightly more prevalent among unemployed women than men (respectively 3.9% and 2.8%). Unemployed women in Greece, Spain and Italy are much more likely than men to find themselves without work for more than twelve months. In contrast, in the United Kingdom and Ireland, a larger proportion (practically double) of unemployed men than unemployed women is jobless for a lengthy period. rate, after remaining stable for three years. Put another way, the proportion of unemployed people without work for at least twelve months decreased for the Union as a whole. In Spain and Ireland, the proportion of long-term unemployed people decreased most since 1997 while there was little change in Denmark and Austria, where it was already a low 1-2%. … also among young people the proportion has fallen The long-term unemployment rate for young people, which uses a threshold of six months or more, stood at 6.9% in 2001, a considerable reduction from the 1994 peak of 13.1% and indeed from the 1998 figure of 11.0%. Young people in Greece and Italy are particularly affected by long-term unemployment (respectively 18% and 21% of the labour force) as indeed are people aged 25 and over in these two countries. The EU long-term unemployment rate fell over the period 1997-2000 more than the overall unemployment Over the period 1994-2000, the proportion of young unemployed people without work for at least 6 months decreased. In 2001, 47% of young unemployed people had been without a job for six months or more, compared with around 64% in 1994. In Greece and Italy, this applied to 64% and 74% of the young unemployed in 2001 compared with around 15% in Denmark and Finland. Policy context Links to other parts of the report (See Employment Guideline N° 2 – fiche 9). Education outcomes (3.5), Employment (3.7), Unemployment (3.9), Youth unemployment (3.10), Labour Market Policy expenditure (3.14), Labour market (Annexes II and IV) The proportion of long-term unemployed decreases Methodological notes Source: Eurostat - Harmonised unemployment rates and European Union Labour Force Survey (LFS). Unemployment is defined according to the ILO definition. See Unemployment (3.5) for definition. The unemployed are counted as long-term unemployed if they have been jobless for at least twelve months. The longterm unemployment rate is calculated by dividing the number of persons unemployed for twelve months or more by the active population in the labour market (or labour force) of the same age and multiplying by 100. For the age-group 15-24, the threshold is lowered to six months or more. Data on the long-term unemployed are also presented in relation to the total number of unemployed people. 138 Further reading ● ● ● ● “European social statistics - Labour force survey results 2000”, Eurostat. “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. Statistics in Focus (Population and Social Conditions): “Dynamic Measures of Economic Activity and Unemployment: 1. Patterns and Transitions over Time", No.17/1999. "Dynamic Measures of Economic Activity and Unemployment: 2. Status in terms of the amount of time spent", No.18/1999. Eurostat. “Employment precarity, unemployment and social exclusion", European Commission DG Research report 2000. Areas of social policy concern - Statistical portraits Section 3 Key indicator EU 15 B DK D EL E F IRL Long-term unemployment rate (Total long-term unemployed (over 12 months) as a percentage of total active population - harmonised series.) 3.2 3.3 0.9 3.9 5.4 5.1 2.9 1.3 2001 - total 2.8 : 0.8 : 3.2 3.0 : 1.6 2001 - males 3.9 : 1.0 : 8.7 8.1 : 0.8 2001 -females 3.7 3.8 1.0 4.0 6.1 5.9 3.7 1.6 2000 5.2 5.6 2.9 3.8 4.4 12.9 4.7 9.4 1994 Source: Eurostat - Quarterly Labour Force Data (QLFD) I L NL A P FIN S UK 5.9 4.5 8.0 6.4 6.7 0.5 : : 0.5 0.9 0.8 0.7 1.0 1.1 3.1 0.9 0.9 1.0 1.0 1.0 1.5 1.2 1.9 1.6 2.6 2.5 2.7 2.3 2.8 6.1 1.2 1.4 1.0 1.7 2.5 1.3 1.7 0.8 1.5 4.2 Persons unemployed for 12 months or more as a percentage of total unemployed 43.8 49.5 21.0 50.2 51.5 47.9 33.7 32.9 2001 47.0 55.1 22.8 51.2 54.9 52.4 40.1 39.1 2000 49.7 56.8 37.7 46.4 49.1 65.1 40.1 65.6 1994 Source: Eurostat - European Union Labour Force Survey (LFS) and Quarterly Labour Force Data (QLFD) 62.5 61.8 61.0 26.3 23.4 29.0 35.3 39.6 46.1 26.2 26.5 25.2 36.5 39.1 37.5 27.6 28.8 36.8 24.5 28.5 26.3 25.4 27.6 44.8 Youth long-term unemployment rate (6 months or more) 6.9 : 1.1 2001 7.7 7.8 0.5 2000 13.1 12.8 3.4 1994 Source: Eurostat - European Union Labour Force Survey (LFS) 21.0 22.5 25.1 : 1.8 4.1 2.5 3.1 10.0 2.0 1.6 1.7 3.7 3.2 7.1 3.1 3.8 7.6 2.3 2.5 10.0 3.0 3.3 8.0 54.0 54.0 34.5 31.4 40.0 37.5 15.9 17.9 27.5 28.4 25.1 27.0 : 3.7 4.4 17.9 20.3 19.3 11.9 12.9 30.2 : 8.3 13.9 : 0.5 17.0 Young persons unemployed for 6 months or more as a percentage of total number of young unemployed persons 47.3 : 12.6 : 63.5 48.2 : : 74.3 : 2001 48.5 44.7 7.6 44.0 68.7 49.1 42.6 7.4 72.4 27.3 2000 Source: Eurostat - European Union Labour Force Survey (LFS) Graph 21 Unemployment rates by duration, 2001 14 Graph 22 Youth unemployment rates by duration, 2001 14 % Less than 12 months 12 months or more 12 35 35 % Less than 6 months 6 months or more 12 30 10 10 25 25 8 8 20 20 6 6 15 15 4 4 10 10 2 2 5 5 0 0 EU-15 B DK D EL E F IRL I L NL A P FIN S 0 UK Source: Eurostat - Quarterly Labour Force Data (QLFD) EU-15 B DK D EL E F IRL I L NL A P FIN Source: Eurostat - European Union Labour Force Survey (LFS) 139 S 30 UK 0 Section 3 Areas of social policy concern - Statistical portraits 12 Social protection expenditure and receipts In 2000, social protection expenditure in the European Union dropped back in real terms and amounted to 27.3% of GDP, down by nearly a whole percentage point compared with 1996. There are considerable differences between Member States : in terms of per-capita PPSs the ratio of the expenditure between the countries that spent most and least within EU-15 in 2000 was thus 2.5. Different countries have markedly different systems for financing social protection, depending on whether they favour social security contributions or general government contributions. Significant rise until 1993, then slight decrease The decline in social protection expenditure as a percentage of GDP continued in EU-15 in 2000 (27.3% in 2000, down by 1.5 percentage points compared with the peak year 1993).Changes in this ratio did not follow a regular pattern over the period 1991-2000. Between 1991 and 1993 the ratio showed an appreciable increase, rising by 2.4 percentage points to a high for EU-15 in 1993 of 28.8%. This was due both to a slowdown in GDP growth and to an increase in benefits (particularly those related to unemployment). The rise was particularly large in Finland, as the country was in recession during that period. Between 1993 and 1996, social protection expenditure as a proportion of GDP levelled off at slightly below the 1993 level. This was the result partly of renewed growth in GDP, but also of slower growth in social protection expenditure (particularly in connection with the reduction in unemployment benefits). From 1996 onwards, social protection expenditure as a proportion of GDP fell steadily, with an average drop of 0.3 percentage points per year in EU-15, and it was in 2000 at a lower level than in 1992.The decline in expenditure as a percentage of GDP between 1996 and 2000 was most marked in Finland (-6.4 percentage points) and in Ireland (-3.7 points). It is worth noting that in Ireland changes in the ratio can to a large extent be explained by the strong growth in GDP in recent years. Slowdown in real-terms expenditure in 2000 Real-terms expenditure on social protection (i.e. in constant prices per head of population) grew by around 1.7% annually during the period 1995-2000 in EU-15. The rise was particularly marked in Greece (7.4% per year) and Portugal (4.9% per year). In Denmark and the Netherlands, on the other hand, per-capita expenditure increased in real terms over the period by less than 1% per year. Lastly, per-capita expenditure in Finland stayed at the same level. In 2000, however, there was a slight easing of the trend in per-capita expenditure, affecting in particular Finland, Belgium, Denmark and Germany. 140 Cross-country differences are more marked when expenditure is expressed in PPS per head of population The average figure for social protection expenditure as a percentage of GDP in EU-15 (27.3% in 2000) conceals wide disparities from one Member State to another.Sweden (32.3%), France (29.7%) and Germany (29,5%) had the highest percentages and Ireland the lowest (14.1%). In terms of per-capita PPSs (purchasing power standards), the differences between countries are more pronounced, and the rank order of countries is somewhat different. Within EU-15, Luxembourg had the highest expenditure (9 235 PPS per head of population), followed by Denmark (7 754 PPS per head). Spain and Portugal, on the other hand, featured a low level of social expenditure, with less than 4 000 PPS per head of population.The ratio between the countries that spent most and least within EU-15 in 2000 was thus 2.5 (compared with 3.2 in 1991). The disparities between countries are partly related to differing levels of wealth and also reflect differences in social protection systems, demographic trends, unemployment rates and other social, institutional and economic factors. Two patterns of funding social protection At EU level, the main sources of funding for the social protection system are social contributions (employers and protected persons), which accounted for 60.7% of total receipts in 2000, followed by tax-funded general government contributions (35.8%). The European average conceals considerable differences between the Member States in the structure of funding. The share of funding derived from social contributions is highest in Belgium, Spain, France, the Netherlands and Germany, where this mode of financing accounts for over 65% of all receipts. In contrast, Denmark, Ireland, and to a lesser extent Luxembourg, Sweden and the United Kingdom are more dependent on taxes to finance their social protection systems. Areas of social policy concern - Statistical portraits Section 3 General government contributions taking over from social contributions between 1991 and 2000. It diminished in all countries, with the exception in particular of the Netherlands, Belgium and Denmark, though Denmark was still the country with the lowest figure.The share accounted for by social contributions paid by protected persons also diminished between 1991 and 2000, from 23.6% to 22.4% for EU-15. The proportion of general government contributions in total funding rose by 4.9 points between 1995 and 2000 for EU-15. While in France and Italy general government contributions increased by more than the European average, in Denmark and the Netherlands their share in total receipts fell substantially as a result of increases in social contributions. The share accounted for by employers’ social contributions fell in EU-15 by 3.1 percentage points For information on the structure of expenditure on social benefits, see Social benefits (3.13). Policy context Methodological notes The EC Treaty (Article2) states that "the Community shall have as its task … to promote throughout the Community … a high level of … social protection." Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS). Social protection encompasses all interventions from public or private bodies intended to relieve households and individuals of the burden of a defined set of risks or needs, provided that there is neither a simultaneous reciprocal nor an individual arrangement involved. The risks or needs that may give rise to social protection are classified by convention under eight "social protection functions". See Social benefits (3.13). Excluded are all insurance policies taken out on the private initiative of individuals or households solely in their own interest. The 2000 data are provisional for B, D, EL, E, F, I, NL, P, FIN, S and UK. The Lisbon European Council of March 2000 attached great importance to the role of social protection systems in the achievement of the overall strategic objective it established. It set out the objective that the European social model, with its developed systems of social protection, must underpin the transformation to the knowledge economy. It went on to state that these systems need to be adapted as part of an active welfare state to ensure that work pays, to secure their long-term sustainability in the face of an ageing population, to promote social inclusion and gender equality, and to provide quality health services. Purchasing Power Parities (PPP) convert every national monetary unit into a common reference unit, the purchasing power standard (PPS), of which every unit can buy the same amount of consumer goods and services across the Member States in a given year. In its progress report to the Feira Summit of June 2000, the High Level Working Party on Social Protection underlined the importance of the role of social protection by stating that it "must form the third side of a triangle, the other, interrelated but separate sides of which are macro-economic policy and employment policy; in this context the role of social protection as a productive factor should be strengthened, in the context of affirmation of the European social model". Links to other parts of the report Social benefits (3.13), Labour Market Policy expenditure (3.14), Income distribution (3.15), Social protection (Annexes II and IV) One of the objectives of the Social Policy Agenda (COM(2000) 379 final) is "to modernise and improve social protection to respond to the transformation to the knowledge economy, change in social and family structures and build on the role of social protection as a productive factor." (Section 4.2.1.1). Further reading ● ● ● 141 “European social statistics - Social protection. Expenditure and receipts 1991-2000”, 2003. Methodology: "ESSPROS Manual 1996", Eurostat. Statistics in Focus (Population and social conditions): "Social Protection in Europe", No. 3/2003. Eurostat. “Social Protection in Europe 2001", 2002. "Social Protection in the Member States of the European Union - Situation on 1 January 1998 and evolution", 1998. European Commission, Employment and Social Affairs DG. Section 3 Areas of social policy concern - Statistical portraits Key indicator EU-15 B DK Expenditure on social protection as a percentage of GDP 2000 1996 1991 27.3 28.4 26.4 26.7 28.6 27.1 28.8 31.4 29.7 D EL E F IRL I L NL A P FIN S UK 29.5 29.9 26.1 26.4 22.9 21.6 20.1 21.9 21.2 29.7 31.0 28.4 14.1 17.8 19.6 25.2 24.8 25.2 21.0 24.0 22.5 27.4 30.1 32.6 28.7 29.5 27.0 22.7 21.2 17.2 25.2 31.6 29.8 32.3 34.7 34.3 26.8 28.1 25.7 Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS) Graph 23 Expenditure on social protection per head of population, 2000 10000 9000 Graph 24 Social protection receipts by type as a percentage of total receipts, EU-15, 2000 10000 PPS General Government contributions 35.8% 9000 8000 8000 7000 7000 6000 6000 5000 5000 4000 4000 3000 3000 2000 2000 1000 1000 0 Employers' social contributions 38.3% Social contributions of protected persons 22.4% 0 P E EL IRL FIN I UK EU-15 B F NL D S A DK Other receipts 3.5% L Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS) Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS) 142 Areas of social policy concern - Statistical portraits Section 3 13 Social benefits In most Member States in 2000, the largest share of social protection expenditure was assigned to the old age and survivors functions. This was especially true of Italy (63.4% of total benefits against the EU average of 46.4%). EU-wide, benefits paid under the old-age and survivors functions rose by 12% in real terms per capita during the period 1995-2000 against +9% for all benefits. This growth is primarily explained by demography. Furthermore the retirement policy also influences the development of these benefits. The old-age and survivors functions account for the major part of benefits the duration of benefits and the level of unemployment benefit. In 2000, benefits linked to the old-age and survivors functions made up the largest portion of social protection expenditure in most Member States, accounting for 46.4% of total benefits in EU-15 as a whole, or 12.1% of GDP. Differing patterns of growth in social benefits Between 1995 and 2000, social benefits rose showed different rates of growth for the various functions. The variations result from evolving needs and changes in the legislation on social protection. This was particularly true for Italy, where more than 60% of total benefits were devoted to these functions. A contributory factor here was the high percentage of the population aged 60 or over (23.9% against an average of 21.7% in EU-15). In Greece, Austria and the United Kingdom these benefits also accounted for more than the European average (almost 50% of the total). In Ireland, on the other hand, less than 30% of benefits came under the “old-age” and “survivors” headings. This is partly due to the fact that the population of Ireland is the "youngest” in Europe: 30.8% of the population was aged under 20 in 2000 (against an EU-15 average of 23%) and barely 12.6% were over 60. It is therefore to be expected that in Ireland expenditure on family and child benefits are amongst the highest in the Union. Total benefits rose by 9% in rea l termes (i.e. in constant prices per head of population) at EU level between 1995 and 2000. Per-capita expenditure on the old age and survivors functions in EU-15 increased by 12% in real terms between 1995 and 2000 (i.e. 2.3% per year). The increase was more marked (more than 6% per year in real terms) in Portugal and Greece, particularly between 1997 and 1998 in Greece, when new benefits were introduced. In general, however, the year 2000 saw a slowdown in the growth of this expenditure in EU-15 (+1.4% in 2000 compared with an average of 2.3% per year over the whole period). The reduction in the rate of growth was particularly marked in Greece, Sweden, Italy and France. In the United Kingdom (+8.7%) and Portugal (+7.1%), on the other hand, in 2000 this expenditure continued to rise more rapidly than in the other countries. Faced with an ageing population (the percentage of people aged 60 or over rose from 20.6% in 1995 to 21.7% in 2000), several countries are in the process of reforming their retirement systems, and the effects of these reforms should gradually make themselves felt. The sickness/healthcare function accounted for more than 27% of all benefits. It outweighed the old age and survivors functions in Ireland. In contrast, Denmark devoted only 20% of total benefits to this function. The family/children function accounts for 8.2% of all benefits in EU-15. Expenditure amounted to at least 13% of total benefits in Luxembourg, Denmark and Ireland. In Spain, Italy and the Netherlands, on the other hand, benefits related to this function amounted to less than 5% of total social benefits. With an average increase in total benefits per head of population of 9.5% in real terms between 1995 and 2000, the sickness/health-care function had a lower growth rate. From 1998 onwards, however, per-capita health expenditure increased more rapidly than total social benefits in all countries except Austria and Portugal. Major disparities between Member States are found with regard to the importance of benefits relating to unemployment: while the average for EU-15 was 6.3% of total benefits, the share in the total amounted to some 12% for countries such as Spain and Belgium. Conversely, Italy, Luxembourg, Portugal, and the United Kingdom devoted less than 4% of expenditure to this function. It is worth noting that the scale of unemployment benefits does not always correlate with the level of unemployment in the various countries, as there are substantial differences in coverage, Expenditure for the family/children function increased more rapidly than that for the other functions, due to upgrading and extension of benefits. This growth (+17.2% in real terms between 1995 and 2000) was more pronounced in 1996, the year in which Germany in particular introduced reforms and extended the system of family benefits. 143 Section 3 Areas of social policy concern - Statistical portraits Expenditure related to the unemployment function fell by 14.5% in real terms in EU-15 between 1995 and 2000. This reduction was the result partly of a gradual improvement in the economic situation and partly of reforms in the system of benefits in a number of countries, involving restrictions on the period for which benefits are paid and moves towards more restrictive conditions for entitlement to benefits. Policy context quate and sustainable pension provision in the long run. The first set of National Strategy Reports are due in September 2002 and a Joint Report will be drafted by the Commission and the Council Report. In the context of its general remarks underlying the importance of social protection systems and calling for their adaptation, the Lisbon summit in March 2000 mandated the High Level Working Party on Social Protection "as its first priority" to prepare, on the basis of a Commission Communication, a study on the future evolution of social protection systems from a long-term point of view, giving particular attention to the sustainability of pensions systems. As requested, the Commission adopted on 11 October 2000 a Communication (COM (2000) 622 final) on the "Future Evolution of Social Protection from a Long-Term Point of View : Safe and Sustainable Pensions". Section 2.6 states that it is for "Member States to decide what pension system they want and what policy mix is required to maintain adequate incomes for older people without jeopardising the stability of public finances, undermining employment incentives or squeezing out other essential public expenditures. However, … Member States face common challenges … (and) share common objectives with regard to pension systems and are committed to a number of principles, amongst which are equity and social cohesion … The Commission therefore invites Member States to co-ordinate their efforts and exchange views and information on practices and reforms in progress or at a planning stage." In a progress report to the Nice Summit of December 2000, the High Level Working Party committed Member States to prepare national contributions, not later than 15 February 2001, on their strategies to ensure the fundamental objectives of their pension systems while ensuring their sustainability in the face of the demographic challenge. The Göteborg European Council in June 2001 stressed the need for a comprehensive approach in order to meet the challenges of an ageing society and endorsed the three broad principles for securing the long-term sustainability of pension systems: to safeguard the capacity of pension systems to meet their social aims of providing safe and adequate incomes to retired persons; to ensure the financial sustainability of pension systems; to enhance the ability of pension systems to respond to the changing needs of society and individuals. The Laeken European Council endorsed the proposition of objectives and working methods in order to apply the open method of co-ordination in the domain of pensions policy. The integrated framework for policy cooperation in this field aims to help Member States to develop their own national strategies for securing ade- 144 The Laeken European Council (2001) called for a similar approach in the field of healthcare and care for the elderly. The long term objectives presented in the Communication of the Commission (COM (2001) 723) are: accessibility, quality and financial viability of health and care systems. Particular attention will have to be given to the impact of European integration on Member States' healthcare systems. See also Social protection expenditure and receipts (3.12). Methodological notes Source: Eurostat - European system of integrated social protection statistics (ESSPROS). See Social Protection expenditure and receipts (3.12). Social benefits are recorded without any deduction of taxes or other compulsory levies payable on them by beneficiaries. "Tax benefits" (tax reductions granted to households for social protection purposes) are generally excluded. Social benefits are divided up into the following eight functions: Sickness/healthcare, Disability, Old age, Survivors, Family/children, Unemployment, Housing, Social exclusion not elsewhere classified (n.e.c.). The Old age function covers the provision of social protection against the risks linked to old age: loss of income, inadequate income, lack of independence in carrying out daily tasks, reduced participation in social life, and so on. Medical care of the elderly is not taken into account (reported under Sickness/healthcare function). Placing a given social benefit under its correct function is not always easy. In most Member States, a strong interdependence exists between the three functions Old age, Survivors and Disability. For the purposes of better EU-wide comparability, the Old age and Survivors functions have been grouped together. F, IRL and P record disability pensions paid to persons of retirement age as benefits under the disability function as opposed to the old age function. Links to other parts of the report Ageing of the population (3.3), Employment of older workers (3.8), Social protection expenditure and receipts (3.12), Social protection (Annexes II and IV) Areas of social policy concern - Statistical portraits Section 3 Further reading ● ● ● ● “European social statistics - Social protection. Expenditure and receipts 1991-2000”, 2003. Methodology: "ESSPROS Manual 1996", 1996. Eurostat. Statistics in Focus (Population and social conditions): "Social Protection in Europe", No. 3/2003. "Social protection in Europe: expenditure on pensions", No.6/2002. Communication (COM 2000-622 final) on the "Future Evolution of Social Protection from a Long-Term Point of View : Safe and Sustainable Pensions". European Commission. ● ● ● “Social protection for dependency in old age in the 15 EU Member States and Norway", 1998. European Commission, Employment and Social Affairs DG. Objectives and working methods in the area of pensions -Joint report of the Social Protection Committee and the Economic Policy Committee - November 2001 Supporting national strategies for safe and sustainable pensions through an integrated approach – COM (2001) 362 The future of healthcare and care for the elderly:guaranteeing accessibility, quality and financial viability COM (2001) 723 Key indicator EU 15 B DK D EL Old age and survivors benefits as a percentage of total social benefits 46.4 44.6 2000 1991 43.8 41.8 38.1 35.8 42.2 42.9 49.4 52.9 E F IRL I L NL A P FIN S UK 46.3 41.4 44.1 42.8 25.4 29.6 63.4 58.7 40.0 47.5 42.4 37.3 48.3 49.9 45.6 40.8 35.8 32.8 39.1 : 47.7 43.7 Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS). Graph 25 Social benefits by groups of functions as a percentage of total benefits, EU-15, 2000 Graph 26 Old age and survivors benefits as a percentage of total social benefits, 2000 70 70 % Unemployment 6.3% Disability 8.1% Old age and survivors 46.4% Housing and social exclusion n.e.c. 3.7% Sickness/healthcare 27.3% Family and children 8.2% 60 60 50 50 40 40 30 30 20 20 10 10 0 0 EU-15 B Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS) DK D EL E F IRL I L NL A P FIN S UK Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS) 145 Section 3 Areas of social policy concern - Statistical portraits 14 Labour Market Policy expenditure In 2000, Labour Market Policy expenditure represented 2.04% of GDP, out of which 0.68% was dedicated to active labour market policy measures. There are considerable differences between Member States that are not a clear north/south divide. Two countries spent more than 3% of GDP (Belgium and Denmark), six countries spent between 2% and 3% (Germany, Spain, France, the Netherlands, Finland and Sweden), and six countries have spent less than 2% (Greece, Ireland, Italy, Austria, Portugal and the United Kingdom). Targeted policies Labour market policies are by definition restricted in scope, covering only those political interventions targeted at the unemployed and other groups of people with particular difficulties in entering or retaining their position in the labour market. Primary target groups in all countries (with the exception of Italy) are the unemployed who are registered with the public employment services. However, public expenditure on LMP should not be interpreted exclusively as demonstrating the strength of the political will to combat unemployment. Other factors such as the demographic situation and the GDP per capita of each country contribute to the differences. Active and passive expenditure Expenditure on targeted programmes including training, job rotation/job-sharing, employment incentives, integration of the disabled, direct job creation and start-up incentives (categories 2-7 of the LMP database) are usually considered as active expenditure, whereas expenditure on out-of-work income maintenance (mostly unemployment benefits) and on early retirement (categories 8-9) is considered as passive expendi- Policy context ture. However, it should be taken into account that in the past few years the conditions for maintaining eligibility to receive unemployment benefits have been increasingly tied to individualised job-search activities and may also involve active intervention by the public employment service. Distribution of active labour market expenditure by type of action Expenditure is highest on training programmes, accounting for 34.5% of expenditure on active measures. Direct job creation is the second most important category, accounting for 27.4%. Expenditure on employment incentives, which includes not only subsidies but also reduction in taxes and social contributions to employers, amounts to 18.8% of expenditure in active categories. Expenditure in the integration of the disabled represents 15.6% of active expenditure, however it should be kept in mind that apart from targeted measures only aimed at disabled people, most countries implement general employment measures which also benefit disabled people. Start-up incentives represent 3% of active expenditure and job rotation/job sharing is the smallest category in terms of expenditure with only 0,8% of active expenditure. The classification categories by type of action referred to in the graphs presented in this article include: The LMP data collection was developed as an instrument for the follow-up of the targeted employment policies implemented by EU countries as a result of the "Jobs Summit" held in Luxembourg in November 1997, which launched the European Employment Strategy with a medium term objective of reducing unemployment. The LMP database has been developed over the past years by Eurostat in close co-operation with DG Employment and Social Affairs, all EU Member States and Norway, as well as the OECD. Methodological notes The scope of the LMP database refers to Public interventions in the labour market aimed at reaching its efficient functioning and to correct disequilibria and which can be distinguished from other general employment policy measures in that they act selectively to favour particular groups in the labour market. 146 Categories 2-7: 2 - Training: Programmes which aim to improve the employability of the unemployed and other target groups through training, and which are financed by public bodies. Measures included here should include some evidence of classroom teaching, or if in the workplace, supervision specifically for the purpose of instruction. 3 - Job rotation and job sharing: Programmes that facilitate the insertion of an unemployed person or a person from another target group into a work placement by substituting hours worked by an existing employee. 4 - Employment incentives: Programmes which facilitate the recruitment of unemployed persons and other target groups, or help to ensure the continued employment of persons at risk of involuntary job loss. The majority of the labour cost is normally covered by the employer. Areas of social policy concern - Statistical portraits Section 3 5 - Integration of the disabled: Programmes that aim to promote integration of disabled persons into the labour market. 6 - Direct job creation: Programmes that create additional jobs, usually of community benefit or socially useful, in order to find employment for the long-term unemployed or persons otherwise difficult to place. The majority of the labour cost is normally covered by the public finance. 7 - Start-up incentives: Programmes that promote entrepreneurship by encouraging the unemployed and target groups to start their own business or to become self-employed. Note that data on category 1 "Intensive counselling and job-search assistance" are not included here because the data are too incomplete. Similarly, data on sub-category 2.4 "Special support to apprenticeship" are presented separately, since data are not fully comparable. Categories 8-9: 8 - Out-of-work income maintenance: Programmes which aim to compensate individuals for loss of wage or salary through the provision of cash benefits when: ● a person is capable of working and available for work but is unable to find suitable employment. ● a person is on lay-off or enforced short-time work or is otherwise temporarily idle for economic or other reasons (including seasonal effects). ● a person has lost his/her job due to restructuring or similar (redundancy compensation). 9 - Early retirement: Programmes which facilitate the full or partial early retirement of older workers who are assumed to have little chance of finding a job or whose retirement facilitates the placement of an unemployed person or a person from another target group. ● Links to other parts of the report Unemployment (3.9), Youth unemployment (3.10), Long-term unemployment (3.11), Old age benefits (3.13), Social protection (Annexes II and IV) Further reading ● ● ● ● ● Labour Market Policy Database - Methodology, April 2000 - Eurostat Working Papers Labour Market Policy Database - Glossary, DE/ENES/EN-FR/EN-IT/EN - Eurostat Working Papers European Social Statistics - Labour Market Policy Expenditure and Participants - Data 1998 - Detailed Tables. Eurostat. European Social Statistics - Labour Market Policy Expenditure and Participants - Data 1999 - Detailed Tables. Eurostat. European Social Statistics - Labour Market Policy Expenditure and Participants - Data 2000 - Detailed Tables. Eurostat. Statistics in Focus (Population and social conditions) : “Public expenditure on Labour Market Policies in 1999 varied greatly among Member States”, No. 12/2002. Eurostat Key indicator EU-15 B DK D EL Public expenditure on active LMP measures as a percentage of GDP, 2000 E F IRL I L NL A P FIN S UK Categories 2-7 excl. 2.4 0.681 1.000 1.641 0.917 0.253 0.632 0.931 0.929 0.436 : 0.920 0.365 0.254 0.742 1.507 0.089 Sub-category 2.4 Categories 8-9 Total 0.075 1.282 2.037 2.178 3.177 0.026 2.378 4.045 0.061 1.924 2.901 0.016 0.449 0.718 1.393 2.025 0.109 1.401 2.441 0.018 0.786 1.733 0.135 0.611 1.182 0.036 0.439 : 0.040 1.890 2.850 0.033 1.204 1.602 0.098 0.876 1.228 0.023 2.093 2.859 1.409 2.916 0.104 0.434 0.627 Categories 2-7: Training - Job rotation and job sharing - Employment incentives - Integration of the disabled - Direct job creation - Start-up incentives Sub-category 2.4: Special support for apprenticeship. Categories 8-9: Out of work income maintenance and support - Early retirement Source: Eurostat - Labour Market Policy Database (LMP) Graph 27 Total public expenditure on LMP measures as a percentage of GDP, 2000 4,5 Graph 28 Labour Market Policy expenditure by type of action (categories 2-7), EU-15, 2000 4,5 Categories 2-7 excl. 2.4 Sub-category 2.4 Categories 8-9 4,0 3,5 3,5 3,0 3,0 2,5 2,5 2,0 2,0 1,5 1,5 1,0 1,0 0,5 0,5 0,0 0,0 EU-15 B DK D EL E F IRL I L NL A P FIN S Start-up incentives 3.0% 4,0 Training (excl. sub-category 2.4) 34.5% Direct job creation 27.4% Integration of the disabled 15.6% Job rotation and job sharing 0.8% Employment incentives 18.8% UK Source: Eurostat - Labour Market Policy Database (LMP) Source: Eurostat - Labour Market Policy Database (LMP) 147 Section 3 Areas of social policy concern - Statistical portraits 15 Income distribution As a population-weighted average in EU Member States in 1999 the top (highest income) 20% of the population received 4.6 times as much of the total income as the bottom (lowest income) 20% of the population. This gap between the most and least well-off people is smallest in Denmark and Sweden (3.2), followed by Finland, Germany, Netherlands and Austria. It is widest in the southern Member States, Ireland and the United Kingdom. Member States with lower levels of average income tend to have higher levels of inequality Regional disparities in terms of Employment Rates In 19995, the median6 equivalised net annual income was around 12,100 PPS (EU-15 population weighted arithmetic average of individual national values). In seven Member States, including Germany and France, the level was over 13,000 PPS: UK is close behind with 12,800 PPS. Luxembourg is an outlier with 20,900 PPS, followed by Denmark with 15,700 PPS. A north/south divide remains apparent, with income levels in Greece, Spain, Italy and Portugal ranging between 7,300 and 10,500 PPS. Ireland, Finland and Sweden were also below the EU average, albeit with incomes above 11,000 PPS. A key indicator in the analyses of labour market economics, at both national and regional levels, is the employment rate, defined as the number of persons in employment as a percentage of the population of working age. In a European context, it is commonly agreed to set an age limit of 15 to 64 years for these variables. Employment rates are available by sex and by age groups at national level. At regional level, however, there is no age breakdown. Regional figures are provided by Eurostat down to NUTS level 2, based on the results of the Community Labour Force Survey. Given that the European Union set targets with respect to employment rates at its Lisbon summit in 2000, it is clear that this rate is of relevance for the policy of the European Union. Income distribution can be measured by looking at how total income is shared among different strata of the population according to the level of income. As a population-weighted average in EU Member States in 1999 the top (highest income) 20% of the population received 4.6 times as much of the total income as the bottom (lowest income) 20% of the population. This indicator, inequality of income distribution, is generally higher in the southern and non-continental Member States (Portugal being the highest with 6.4 - although Greece, Spain, Ireland, Italy and UK also find themselves above the EU average of 4.6). At the other extreme are Denmark and Sweden (3.2), followed by Finland (3.4), Germany (3.6) and Netherlands and Austria (3.7). Another way of looking at income inequality is to compare the Lorenz curve of actual income distribution to the line of perfectly equal income distribution7. Within the EU, the country closest to equality was Denmark (coefficient 0.23) and the furthest away was Portugal (0.36) with an EU average coefficient of 0.29. In general, Member States with higher levels of inequality tend to have a lower level of average income (although the United Kingdom has both above average income and above average inequality). 5 6 7 If the intention is to measure the regional disparity of regional employment rates for countries or for the European Union as a whole, a choice has to be made between the various measures of regional disparity. In this chapter, regional disparities are measured by the Coefficient of Variation (CV) of employment rates. It goes without saying that it is not possible to apply the standard formula for a CV. Instead, the size of the regions has to be taken into account in this calculation (see also methodological explanations). This indicator should be interpreted with care, because it is an indicator of indicators, aggregating over the regional dimension. Therefore, a lot of information is included in one figure. This indicator is also quite sensitive to small changes in the original rates, whenever these small changes show a regional bias. Unfortunately, regional employment rates are only available down to NUTS level 2, implying in some cases a limited number of observations. Again, therefore, the figures should be interpreted with care. Despite its shortcomings, the CV of regional employment rates is included in the list of Structural Indicators that were requested from the European Commission by the European Council meeting in Lisbon in 2000. The latest (December 2002) release of the European Community Household Panel user database (wave 6: years 1994-1999) incorporates major improvements by comparison to previous editions. These relate to the country coverage (all 15 Member States of the EU), to the data supplied by two national data units (UK and Belgium) and to the methodology employed to establish weightings and to impute for item non-response. For these reasons, resulting indicators cannot be considered to be comparable with those established on the basis of the preceding user database (wave 5, December 2001). Data for Spain should be treated as provisional, pending a planned revision of weightings to be introduced for wave 7. Data for certain countries (eg. Germany, UK) continues to be derived from national panels reformatted for ECHP purposes. The median value is generally preferred as the measure of central tendency of incomes since it is less affected by values at the extremes of the distribution (rich and poor). For comparison, the mean value for 1999 was 13,770 PPS. This can be expressed mathematically as the Gini coefficient (a mathematical expression of the ratio of the amount of graph between the line of perfectly-equal distribution and the curve of actual distribution to the total amount of graph below the line of perfectly-equal distribution). 148 Areas of social policy concern - Statistical portraits Section 3 Besides its purpose of serving as a measure of regional dispersion, it can also be seen as a quality criterion of the targets that have been defined for the employment rates at a European level. It makes it possible to differentiate between countries that have reached an identical national employment rate, but demonstrate different degrees of regional dispersion. Across the countries of the European Union, there are substantial differences in the CV. Italy and Spain show high degrees of regional dispersion of employment rates, whereas in the Netherlands and Austria no big spread of the employment rates can be detected. The differences between the candidate countries are much less evident. Policy context head at NUTS-3 level are taken from Eurostat's regional accounts and are based essentially on the European System of National Accounts (ESA 95). The EC Treaty (Article 2) states that "The Community shall have as its task … the raising of the standard of living and quality of life…". Article 3 continues "the activities of the Community shall include … the strengthening of economic and social cohesion;" Total household income is taken to be all net monetary income received by the household and its members at the time of the interview (1998) during the survey reference year (1997). This includes income from work, private income (e.g., from investments or property), as well as pensions and other social transfers directly received. As in previous years, no account has been taken of indirect social transfers, receipts in kind and imputed rent for owner-occupier accommodation. As the weight of these income components varies between countries, there is some limitation on the full comparability of income statistics. Comparable income data are now available for most countries but are no longer available for Luxembourg or Finland. The Lisbon European Council in March 2000 set itself "a new strategic goal for the next decade: to become the most competitive and dynamic knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion." See also Communication adopted by the Commission in March 2000 entitled "Building an Inclusive Europe". A list of statistical “structural indicators” was agreed at the Nice summit in December 2000, including 7 indicators in the field of social cohesion. This list has been updated for the Synthesis Report from the Commission to the Barcelona Council in March 2002. This approach has been further developed by the Indicators Sub-Group of the Social Protection Committee, who proposed a list of “cohesion indicators” which was adopted by the Laeken summit in December 2001. In order to take account of differences in household size and composition in the comparison of income levels, the household's total income is divided by its 'equivalent size', computed using the modified OECD equivalence scale. This scale gives a weight of 1.0 to the first adult, 0.5 to the second and each subsequent person aged 14 and over, and 0.3 to each child aged under 14 in the household. To calculate the share ratio, persons are first ranked according to their equivalised income and then divided into 5 groups of equal size known as quintiles. S80/S20 represents the sum of the income of the 20% of households with the highest incomes to that of the bottom 20%. For information on NUTS, see notes under Unemployment (3.9). The Social Policy Agenda (COM(2000) 379 final) states that "social transfers covering pensions and social security do not only contribute to balance and re-distribute incomes throughout lifetimes and across social groups, but also support better quality in employment, with consequent economic benefits." The Coefficient of Variation is calculated using employment rates at NUTS level 2. It is calculated for each country separately and gives a measure of the regional spread of employment rates. As the calculation of the Coefficient of Variation is only a formula, it is important to look at the basic data, the employment rates. The employment rate is defined as the number of employed persons, expressed as a percentage of the population of working age (in both cases, the relevant age group is 15 - 64 years). Employed persons are all those in work during the reference period. The rate can be broken down further by age and sex. The Structural Funds are part of the Community's structural policy which is intended to reduce the gap in terms of development between different regions and between Member States and thereby promote economic and social cohesion. Between 1994 and 1999, the Community allocated around 35% of the EU's total budget to structural measures (EUR 208 billion). On 20 June 2001 the Commission published the communication entitled: “Employment and social policies: a framework for investing in quality”. Methodological notes For Denmark, Ireland and Luxembourg, the coefficient of variation of unemployment across regions at NUTS level 2 is not relevant. There is no legal basis regulating the production and dissemination of the Coefficient of Sources: Eurostat - European Community Household Panel (ECHP), wave 6, version December 2002. Income data refers to the calendar year 1997. Data on GDP per 149 Section 3 Areas of social policy concern - Statistical portraits Variation from EU-Member States to Eurostat. The reporting by Member States of data on regional employment and the economically active population forms part of the usual data delivery in the context of the yearly European Community Labour Force Survey. Further reading ● ● Links to other parts of the report ● Social protection expenditure and receipts (3.12), Lowincome households (3.16), Jobless households and low wages (3.17), Income, poverty and social exclusion (Annexes II and IV). ● ● ● Key indicator EU-15 B DK D EL E F “European social statistics: Income, Poverty and Social Exclusion in the Member States of the European Union", 2000 edition. ”European Community Household Panel: selected indicators from the 1995 wave”, 1999. Eurostat. Statistics in Focus (Population and social conditions): "Social benefits and their redistributive effect in the EU", No.9/2000. Eurostat. "Employment in Europe 2000", European Commission, Employment and Social Affairs DG. ”Unity, solidarity, diversity for Europe, it’s people and territory – Second report on Economic and Social Cohesion”, 2001. European Commission. Evaluation of income support policies at the local urban level", European Commission DG Research reports 1999. IRL I L NL A P FIN S UK Inequality of income distribution (income quintile share ratio) - The ratio of total income received by the 20% of the population with the highest income (top quintile) to that received by the 20% of the population with the lowest income (lowest quintile). Income must be understood as equivalised disposable income. 1999 4.6* 4.2 3.2 3.6 6.2 5.7* 4.4 4.9 4.9 3.9 3.7 3.7 6.4 3.4 3.2 5.2 Source: Eurostat - European Community Household Panel - UDB version December 2002 Graph 29 Level of income and income inequality, 1999 Graph 30 Dispersion of regional employment rates, 2001 7 7 Share ratio S80/S20 20 20 % P 16,6 EL 6 6 15 E 14,4 15 UK IRL 5 EU-15 I B FIN 7,8 4 L NL A S 10 12 7,0 6,4 6,1 DK 5 3 2,6 2 8 7,2 5,1 D 2 6 10 10 F 4 3 11,8 5 14 16 18 20 3,1 4,1 3,7 0 0 22 EU-15 B DK D EL E F IRL I L NL A P FIN Median equivalised income (x 1,000 PPS) Source: 5 Source: Eurostat - European Union Labour Force Survey 2001. Eurostat - European Community Household Panel - UDB, version December 2002 150 S UK Areas of social policy concern - Statistical portraits Section 3 16 Low-income households When looking at the total population, around 15% of EU citizens had an equivalised income that was less than 60% of their respective national median in 1999. This figure represents around 56 million people. Using 60% of the national median as a cut-off threshold, the proportion of people at risk of poverty was relatively higher in Greece and Portugal (21%), followed by Spain and the United Kingdom (19%) - and was relatively lower in Belgium, Denmark, Germany, Luxembourg, Netherlands, and Austria and Finland (11 to 13%). It was particularly low in Sweden (9%). Social benefits reduce the proportion of people at risk of poverty in all Member States but to very differing degrees: the reduction ranging from around 5% in Greece to nearly 70% in Sweden. More than one-third of lone parents have a 'low income' Unemployed people most at risk On average, just under 40% of unemployed people have a low income in 1999. The proportion is highest in Ireland (over 50%) and there are higher than average rates in Italy, UK, Spain and Luxembourg. The level is lowest in Denmark (7%), followed by Netherlands (18%), Sweden and Austria (20%). In Ireland, the unemployed are around thirteen times more likely than those people with a job to have a low income. In Denmark, Greece, Netherlands and Portugal on the other hand, the ratio is closer to three. In 1999, certain household types again display higher than average levels of being at risk of poverty: singleparents with dependent children (38%), young people living alone (32%), old people living alone (24%) and women living alone (24%). Couples with three or more dependent children were also at high risk (25%). In 1999 more than 50% of single-parents in Spain and United Kingdom can be classified as having a 'low income'. Levels were also high (around 40%) in Portugal, Netherlands, Ireland and Germany. In 1999 over 30% of households with more than 3 children in Portugal, United Kingdom, Italy, Spain and Luxembourg had a ‘low income’. In 1999 over 50% of young people living alone (age under 30) had a ‘low income’ in Denmark and Finland. There were also levels above the EU average (32%) in Germany, France, Netherlands, Sweden and United Kingdom. More than 60% of old people living alone (aged over 65) had a ‘low income’ in Ireland. Rates were also high (over 50%) in Portugal and Denmark compared with an EU average of 24%. For the Union as a whole, 6% of those at work (not selfemployed) fall into the low income category. See also Jobless households and low wages (3.16). Impact of benefits on the proportion of poor people is significant A comparison of the number of people on low incomes before social benefits other than pensions and after social benefits, i.e. pensions are included in income both 'before' and 'after', illustrates one of the main purposes of such benefits: their redistributive effect and, in particular, their ability to reduce the percentage of the population on low incomes. Women (compared with men) and children (compared with adults) are more likely to be poor Throughout the Union, being at risk of income poverty is slightly more prevalent among women than among men (EU average of 16% versus 15%). The gender gap is noticeably larger among the elderly (aged over 65) – particularly in Germany, Ireland, Austria and United Kingdom. However, some caution is necessary in interpreting these figures due to the assumptions made about how income is allocated within families. Before social benefits other than pensions are taken into account, in 1999 Ireland, and the United Kingdom show a high percentage (30%) of people on low incomes, followed by Sweden and Portugal. The figures for the other Member States range from a lower figure of 21% (Germany, Italy, Netherlands and Finland) with an EU average of 24%. Social benefits reduce the percentage of people at risk of poverty in all the Member States, but to very disparate degrees. The reduction is smallest in Greece, Spain, Italy and Portugal and is highest in Denmark and Sweden. In 1998, the proportion of children (under the age of 16) living in a household with low income (19%) is more than 1/4 higher than for the population as a whole (15%). Children in Spain and United Kingdom seem to be particularly worse off. By contrast, children in Denmark, Greece and Finland are considerably less likely to live in 'poor' households than adults. It is notable that Denmark and Sweden have some of the lowest at-risk-of-poverty rates after payment of pensions and other benefits. By contrast, Greece and Portugal have some of the highest percentages of people on low 151 Section 3 Areas of social policy concern - Statistical portraits incomes after benefits (and Italy moves from being a country with one of the lowest at-risk-of-poverty rates before transfers to about average after transfers). rage at-risk-of-poverty line of 7,263 PPS8 in the European Union, this amounts to a relative poverty gap of roughly 1,600 PPS in equivalised income. Ireland and the United Kingdom have some of the highest at-risk-of-poverty rates in the EU before benefits, and the inequalities remain higher than the Community average after payment of benefits (but the benefits have nevertheless had some redistributive effect). Around 35 million people living in persistent risk of poverty EU poverty gap of 30% Looking at income below the poverty line identifies those people at-risk-of income poverty, but does not show how severe this poverty is. Measuring the gap between the level of income of the poor and the at-risk-ofpoverty threshold provides an insight into the severity of income poverty: the poverty gap. In 1999, half of the people living in a low-income household in the EU had an equivalised household income that was more than 22% below the EU average poverty line. With an ave- Policy context Art.136 of the EC Treaty lists "the combating of exclusion" as one of the six objectives of European social policy. Art.137.1 cites the integration of people excluded from the labour market as one of the fields in which Community action should support and complement the activities of Member States. Art.137.2 creates scope for action at Community level by encouraging "co-operation between Member States through initiatives aimed at improving knowledge, developing exchanges of information and best practices, promoting innovative approaches and evaluating experiences in order to combat social exclusion." The Lisbon European Council in March 2000 concluded that "the number of people living below the poverty line and in social exclusion in the Union is unacceptable" and that "the new knowledge-based society offers tremendous potential for reducing social exclusion" (Presidency conclusion No.32). This conclusion was reinforced at the Nice and Stockholm summits in December 2000 and Spring 2001. The Social Policy Agenda (COM(2000) 379 final) also addresses the issues of poverty and social exclusion. The main objective is "to prevent and eradicate poverty and exclusion and promote the integration and participation of all into economic and social life." (Section 4.2.2.1). 8 In 1999, 9% of the European Union population were living in a low-income household and had been in this situation for at least two of the three preceding years. This figure suggests that more than half of all people in low income households in 1999 are living at-persistent–risk-of-poverty. The at-persistent-risk-of-incomepoverty rate ranges from around 5% in Denmark and the Netherlands to 13% in Greece and 14% in Portugal. Low income doesn’t necessarily by itself imply low living standards. Typically it is the cumulative negative impact of persistent and/or multiple disadvantage, which may lead to poverty and social exclusion. The diverse causes can require specific, less generalised, more effective inclusion strategies. The Lisbon Council agreed that Member States’ policies for combating social exclusion should be based on an open method of co-ordination combining common objectives, National Action Plans and a programme presented by the Commission to encourage co-operation in this field. The Nice European Council in December 2000 adopted the common objectives in the fight against social exclusion and poverty: "to facilitate participation in employment and access by all to the resources, rights,goods and services; to prevent the risks of exclusion; to help the most vulnerable; to mobilise all relevant bodies." The first two yearly plans were adopted by the Member States in June 2001 and the first Joint Inclusion Report which synthesises and analyses these was adopted by the Employment and Social Affairs Council on 3 December 2001. An initial set of ten primary and eight secondary commonly agreed indicators was presented by the Social Protection Committee : these indicators will serve the purpose of monitoring progress towards the common objectives agreed in Nice. Methodological notes Source: Eurostat - European Community Household Panel (ECHP) UDB, wave6, version December 2002. For more details on Purchasing power standards, see “Purchasing power parities and related economic indicators: Results for 1998” (Eurostat, 2000) 152 Areas of social policy concern - Statistical portraits Section 3 The risk or extent of low income poverty (relative, monetary poverty) is measured in terms of the proportion of the population with equivalised income below 60% of the median equivalised income in each country. The median income is preferred to the mean income as it is less affected by extreme values of the income distribution. Further reading ● ● The relative poverty gap is defined as the extra income necessary to bring the equivalised household income of a person who is under the at-risk-of-poverty line, level with the income at the at-risk-of-poverty line. See Income distribution (3.14) for definition of income concepts and notes on data. ● Comparable income data is not available for Finland and Sweden in earlier years, so at-persistent-risk-ofpoverty rates cannot be established. 4-year persistent poverty could not be calculated for Austria in 1997 (3year persistent poverty rate is lower than EU average). No data is available for Luxembourg. ● ”European social statistics: Income, Poverty and Social Exclusion in the Member States of the European Union", 2000 edition. Eurostat. Statistics in Focus (Population and social conditions): "Persistent income poverty and social exclusion in the European Union", No.13/2000. "Income poverty in the European Union: Children, gender and poverty gaps", No.12/2000. "Social benefits and their redistributive effect in the EU", No.9/2000. "Social exclusion in the EU Member States", No.1/2000. "Low income and low pay in a household context (EU-12)", No.6/1998. Eurostat. ”Evaluation of income support policies at the local urban level", European Commission DG Research reports 1999. Joint Report on Social Inclusion - COM (2001) 565 Links to other parts of the report Employment (3.7), Social protection expenditure and receipts (3.12), Income distribution (3.15), Jobless households and low wages (3.17), Income, poverty and social exclusion and Consumption (Annexes II and IV) Key indicator EU 15 B DK D EL E F IRL I L NL A P FIN S At-risk-of-poverty rate - before social transfers. The share of persons with an equivalised disposable income, before social transfers, below the risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income (after social transfers). Retirement and survivor's pensions are counted as income before transfers 24* 25 24 21 22 23* 24 30 21 24 21 23 27 21 28 and not as social transfers, 1999 At-risk-of-poverty rate - after social transfers. The share of persons with an equivalised disposable income below the risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income, 1999 15* 13 11 11 21 19* 15 18 18 13 11 12 60% of median annual income (€) 60% of median annual income (PPS) 7334* 7263* 8 531 11 649 8 659 9 414 8 754 8 236 3 810 4 753 4491* 5347* 8 289 7 944 6 656 6 721 5 557 6 305 12 716 12 532 7 668 8 067 8 621 8 158 UK 30 21 11 9 19 3 168 4 400 8 154 6 921 8 503 6 942 8 289 7 694 Source: Eurostat - European Community Household Panel UDB, version December 2002. Graph 31 At-risk-of-poverty rate (after social transfers) and At-persistent-risk-of-poverty rate, 1999 % 40 25 After transfers 25 Graph 32 At-risk-of-poverty rate after and before social transfers, 1999 Low income 1999 Low income 1999 and during at least two out of the three years 1996 to 1998 20 20 15 15 0% % 30 25% EL 20 10 0 0 S DK NL FIN DK A B L EU-15 F I IRL E UK EL 50% L A B DK D, NL, FIN S 10 5 UK IRL EU-15, F I 10 5 P E Before transfers 0 0 P 75% 10 20 30 40 Source: Eurostat - European Community Household Panel, UDB, version December 2002 Source: Eurostat - European Community Household Panel, UDB, version December 2002 153 Section 3 Areas of social policy concern - Statistical portraits 17 Jobless households and low wages An important cause of poverty and social exclusion is the lack of a job or low wages from employment. In 1999, the 'at-risk-ofpoverty' rate for people living in households where no people of working age are in employment was 51% - nearly 3 times as high as the rate where at least one person is working. Persons living in households where no people of working age are in employment are 2.8 times more likely to be poor than people living in households where at least one person is working In 2002, 12.1% / 8.9% of the EU population aged 0-65 / 0-60 years were living in jobless households, i.e. households where no member was in employment (excluding persons in households where all members are aged less than 18 years, or 18-24 years and in education, or 65 / 60 years and more and not working). The proportion was lowest in Portugal (5.4% / 3.7%). In contrast, Belgium (16.3% / 12.9%)) and the United Kingdom (14.3% / 12.0%) record the highest figures (no data for the three Nordic Member States). EU-wide, the at-risk-of-poverty rate for people living in households where no people of working age are in employment was 51% compared with 18% among households in which at least one person is in employment and 5% where all working age people are in employment. Put another way, people in jobless households are around 2.8 times more likely than those in working households to be living below the poverty line. The difference between these two groups varies significantly between Member States. In Denmark, Germany, Ireland or Finland, those in jobless households are at least five times more likely to be poor while in Greece, France, Italy, Luxembourg, Austria or Portugal, they are only around two times more likely. In 1999, more than half the people in jobless households in Germany, Spain, Ireland, Italy and United Kingdom were living below the poverty line. In contrast, the proportion was considerably lower in Luxembourg (24%) and Austria (26%). Belgium, Denmark, Greece, France, Portugal and Finland all had rates between 41% and 50%. Working poor: a complex picture Although people in employment are less likely to live in a low-income household, i.e. to be "working poor", Policy context The system of financial incentives is one of the main determinants of participation in the labour market and has been an important consideration both for the Employment Guidelines and the BEPGs, and the future EES will place more emphaisis on this issue. The objective 154 the risk of poverty is not removed. An employee's standard of living (as measured by income) is only partly determined by his/her wage. Indeed, in many cases, low wages received by one member of a household are "compensated for" by higher wages received by one or more other members of the household. Similarly, a household may receive income other than wages (income from self-employed work or other types of income such as social benefits, income from property, etc.). Lastly, the standard of living depends not only on the resources available but also on the size of the household as well as its economic (number of people in employment, etc.) and demographic (number of children and other dependants, etc.) characteristics. All low-wage employees do not, therefore, live in low-income households. Inversely, employees whose wages are above the low-wage threshold may - e.g. if they have a number of dependants - be living in poor households. EU-wide, 7% of employees are poor In 1999, for the EU as a whole, the at-risk-of-poverty rate for employees is about 6%. It is considerably higher in Greece and Portugal (9-10%), and is lower in Belgium, Denmark and Finland (2% to 3%). In all the countries analysed, the at-risk-of-poverty rate among employees is – as might be expected – lower than the at-risk-of-poverty rate among the population as a whole. It is not necessarily the countries with the highest at-risk-of-poverty rates that have the highest proportions of employees living at-risk-of-poverty, but this does seem generally to be the case. Denmark has some of the lowest at-risk-of-poverty rates both for the population as a whole and for employees, while Portugal has some of the highest at-risk-of-poverty rates both for the population as a whole and for employees. At EU level and in most countries the at-risk-of-poverty rate of employees is less than half that of the total population for 1999. of "Making work pay" should be pursued both from the point of view of the jobseeker and from that of the employer. In line with the recommendations of the Joint Report on increasing labour force participation, there is a need for a systematic review of tax/benefit systems with a particular focus on eliminating unemployment and poverty traps, encouraging women to enter, remain in or rein- Areas of social policy concern - Statistical portraits Section 3 tegrate into the labour market after an interruption, and on retaining older workers longer in employment.In addition taxation on labour particularly for the low-skilled workers should be such as to reduce the attractiveness of undeclared work and to encourage job creation. Further reading ● See also Low-income households (3.16) ● Methodological notes Sources: Eurostat – European Union Labour Force Survey (data on population living in jobless households). European Community Household Panel (ECHP) UDB, version December 2002,1999 data, wave 6. ● ● See Income distribution (3.15) for income concept and definition of equivalised income. For definition of lowincome (or poor) households, see Low-income households (3.16). Links to other parts of the report ● Employment (3.7), Social protection expenditure and receipts (3.12), Income distribution (3.15), Low-income households (3.16), Income, poverty and social exclusion (Annexes II and IV) ”European social statistics: Income, Poverty and Social Exclusion in the Member States of the European Union", 2000 edition. ”European Community Household Panel: selected indicators from the 1995 wave”, 1999. Eurostat. “Employment in Europe 2002", chapter 3 "Synergies between quality and quantity in European labour markets", September 2002. European Commission, Employment and Social Affairs DG. "Employment in Europe 2001", chapter 4 "Quality in Work and Social inclusion", July 2001. European Commission, Employment and Social Affairs DG. Statistics in Focus (Population and social conditions): "Income poverty in the European Union: Children, gender and poverty gaps", No.12/2000. "Low-wage employees in EU countries", No.11/2000. "Social benefits and their redistributive effect in the EU", No.9/2000. "Social exclusion in the EU Member States", No.1/2000. Eurostat. ”Low pay and earning mobility in Europe", TSER programme. Edward Elgar Publishing UK 1999. Key indicator EU 15 B DK D EL E F IRL I L NL A P FIN Population in jobless households - persons aged 0-65 (Percentage of people living in households with no member in employment as a share of total population (excluding persons in households where all members are aged less than 18 years, or 18-24 years and in education, or 65 years and more and not working)) 12.1 16.3 : 13.8 10.1 8.1 13.1 9.8 11.5 8.9* 9.5* 9.9* 5.4 : 2002 Population in jobless households - persons aged 0-60 (Percentage of people living in households with no member in employment as a share of total population (excluding persons in households where all members are aged less than 18 years, or 18-24 years and in education, or 60 years and more and not working)) 2002 8.9 12.9 : 8.9 7.2 6.2 9.8 8.5 8.5 5.6* 6.3* 6.5* 3.7 : Source: Eurostat - European Union Labour Force Survey 2002. At-risk-of-poverty rates (%) among people living in households where … of the working age people are in employment, 1999 … none … 51.0 43.0 45.0 54.0 42.0 54.0 47.0 79.0 51.0 24.0 : 26.0 … some -but not all- … 18.0 11.0 5.0 10.0 20.0 18.0 21.0 12.0 24.0 16.0 : 13.0 … all … 5.0 3.0 3.0 4.0 11.0 5.0 5.0 3.0 4.0 7.0 : 7.0 Source: Eurostat - European Community Household Panel UDB, version December 2002. Graph 33 Population in jobless households, 2002 41.0 24.0 13.0 47.0 9.0 5.0 S UK : 14.3 : 12.0 : : : 57.0 22.0 7.0 Graph 34 At-risk-of-poverty rates among people living in households where … of the working persons are in employment, 1999 90 18 90 16 80 14 14 70 12 12 60 60 10 10 50 50 8 8 40 40 6 6 30 30 4 4 20 20 2 2 10 10 0 0 0 18 % 0-65 years 0-60 years 16 EU-15 B Source: DK D EL E F IRL I L NL A P FIN S UK % Source: 155 80 70 0 EU-15 B Eurostat - European Union Labour Force Survey none some but not all all DK D EL E F IRL I L NL A P FIN S UK Eurostat - European Community Household Panel UDB, version - December 2002 Section 3 Areas of social policy concern - Statistical portraits 18 Women and men in decision making At the EU level, women's representation in the European Parliament has increased steadily with each election since 1984 and now reaches 30%. In national Parliaments women continue to be under-represented in all Member States as the percentages of seats occupied by women in these bodies range from 9% in Greece to 44% in Sweden. Balanced participation of women and men in decision making is a key element in achieving gender equality and a fundamental requirement for well functioning democracies, which take into account the interests and needs of the whole population. There is however a persisting imbalance in the European Union concerning the participation of women and men at the level of decision making in politics, management, trade unions, universities, civil society and in the judiciary. Women are still far from taking an equal part in the decision making process. To tackle their under-representation is a structural and multifaceted challenge. There is still a way to go in fully implementing the Council Recommendation (2-12/1996) on the balanced participation of women and men in the decision making process (96/694/EC). Ten Member States have now legal provisions in their Constitution or in Gender Equality Acts addressing the issue of gender-balanced decision making to varying degrees. Political decision making In the national parliamentary bodies in spring 2001, only 23% of the seats were occupied by women. The discrepancies between countries were huge, from a minimum share of 9% in Greece to a maximum of 44% in Sweden. On average, 24.1% of cabinet ministers in national governements are women. Sweden has the highest percentage with 52.6 %. It is harder to compare the regional assemblies as some Member States do not have any such bodies. Out of the 9,842 people elected in regional parliaments, 2,896 are women, giving a participation rate of 29% (data reported in 2000). For the local councils in the countries of the European Union, data are incomplete and not always comparable, due to the huge differences in local level political decision-making. Data available for 1997 pointed to a female participation rate near to 20% in these local councils. The European Parliament has presented a slow progression in terms of gender balance during the last years: currently there are 30% of women, while there were only 19% in 1991. Women's representation in the European Commission is 25 %. 9 Participation in the executive bodies In 12 Member States the participation rates of women are higher at the level of the national government than in the national Parliament (or Lower House). The difference is particularly striking in France, with 10% of women in the Assembly and 29% of women in the national government. Considering the regional level, the tendency is different, with a higher participation of women in the regional assemblies (29%) than in the executive bodies: Out of 940 reported members of regional executive structures, 206 are women, reaching a rate of 22%. In a federal state such as Germany, for example, female participation rates in the national and regional assemblies are very similar, reaching 32% and 31% respectively. However, the values are more different for the executive bodies, with 39% and 24% at national and regional levels respectively. The European Commission and some Member States have adopted regulations on balanced participation of women and men in expert groups and committees. The European Commission sets a target of at least 40% of each sex in each group or committee in the medium term. Participation of women in the highest-ranking positions in the public administrations varies from 40% in Sweden to 10% in Austria, Belgium, Germany, Ireland, Italy and Luxembourg. In 2001, at the level of the civil servants of the European Commission, there were 7.4% and 11.3% of women in the two highest levels (A1 and A2 grades) The Employment Committee Report on Indicators of Quality in Work proposes to develop an indicator to measure the share of employed women with supervisory role at work compared with that of men. Balanced participation in decision-making will be helped by better reconciliation between work and family life Reconciliation between work and family life is a key factor in women's accession to decision making posts. A recent study carried out by the Women's Institute9 in Spain shows that women who have acceded to managerial posts are more likely to be single than men, and Instituto de la Mujer (An autonomous public body), “El acceso de las mujeres a los puestos de dirección. The study "Access of women to Executive Post" by Ester Barbera, Professor of Basic Psychology at the Universidad de Valencia, at the request of the Instituto de la Mujer. Such study has not been published yet. 156 Areas of social policy concern - Statistical portraits Section 3 have fewer children than their male counterparts. It further shows that the family may still constitute an important obstacle to the promotion of women to executive posts. local councils in Europe and the difficulties met by women in taking up local mandates. It showed that problems with time management are a significant limiting factor. Fulfilling local mandates often implies time schedules not compatible with raising children, if fathers do not share family responsibilities or adequate and affordable childcare services are not available. A project co-financed by the Gender Equality programme10 discussed the status of elected representatives in Policy context regional or local authorities and organisations that aim to promote gender equality. The Declaration and the Platform for Action of the Fourth World Conference on Women (Beijing, 4-15/9/95) stressed the "need to ensure the responsibilities, powers and rights are shared equally". Methodological notes Data is available on the number of women in parliament and most national governments. The source used here is the European database – Women in decision making – (http://www.db-decision.de). Council Recommendation (2-12/1996) on the balanced participation of women and men in the decision making process (96/694/EC): The Member States were recommended to "adopt a comprehensive integrated strategy designed to promote balanced participation of women and men in the decision making process and develop or introduce appropriate measures to achieve this; . . . improve the collection and publication of statistics to provide a clearer picture of how men and women are represented at all levels of the decision making process in the political, economic, social and cultural spheres; . . . promote a balanced participation of women and men at all levels in governmental bodies and committees; (see the Report from the Commission of COM(2000)120 final from 7.3.2000). Not all countries have conclusive statistics on the participation of women in other decision making bodies. See the Report of the Finnish Presidency on the nine indicators for measuring progress in the field of decision making (SI(1999)873). In 2002, the Commission contracted out the establishment of a European database on women and men in decision-making positions in politics, the economy and the social life in the Member States, EEA countries and the applicant countries to the EU.. Links to other parts of the report Commission Decision relating to Gender Balance within the Committees and Expert Groups established by it (2000/407/EC of 19.6.2000) Education outcomes (3.5), Employment of women and men (3.19), Earnings of women and men (3.20), Gender equality (Annexes II and IV). The Framework Strategy on Gender Equality (20012005) encourages the development of networking of elected women , promotes awareness-raising activities, assess the influence of electoral systems and monitors improvements in the gender composition of committees and expert groups set up by the Commission. Further reading ● The priority theme for the implementation of the Programme on Gender Equality in 2003 is “Women in decision making”. Two calls for proposals were launched in October 2002. The first was a call to governments to organise transnational initiatives such as conferences, campaigns and other activities on women in decision-making. The second call goes out to NGOs or social partners at European level, and networks of ● ● 10 Pourquoi pas conseillères municipales ? Internet: www.ellesaussi.asso.fr 157 Report from the Commission on the Implementation of Council Recommendation 96/694 of 2 December 1996 on the balanced participation of women and men in the decision making process – COM(2000)120 final. Annual Report on Equal Opportunities for Women and Men in the European Union – 2001 – COM(2002)258 final ETAN report on Women and sciences: Promoting excellence through mainstreaming gender equality, 2000. Section 3 Areas of social policy concern - Statistical portraits Key indicator I L NL A P FIN S UK Female share in national parliaments (Percentage of seats occupied by women in the national Parliaments (or Lower House)), 23 23 38 32 9 28 10 13 spring 2001 EU-15 B DK D EL E F IRL 11 17 35 28 20 37 44 18 Percentage of seats occupied by women in the European Parliament, election June 1999 30 28 38 36 16 34 40 33 10 33 32 38 20 44 50 24 Percentage of women in the national governments, spring 2001 25 22 43 39 13 18 29 22 14 29 36 31 10 39 50 33 Source: European database - Women in decision making Graph 35 Percentage of seats occupied by women in Parliaments, 2001 60 % Graph 36 Percentage of women in the national governments, spring 2001 60 60 50 50 50 50 40 40 40 40 30 30 30 30 20 20 20 20 10 10 10 10 National Parliament/Lower House European Parliament 0 F I IRL L UK P EU-15 B E A D NL FIN DK 0 0 0 EL 60 % S EL Source: European database - Women in decision making F I IRL L UK P EU-15 B E A D NL Source: European database - Women in decision making 158 FIN DK S Areas of social policy concern - Statistical portraits Section 3 19 Employment of women and men Between 1996 and 2001, the EU employment rate for men rose by almost 3 points. Over the same period, the rate for women however rose by almost 5 points, thereby narrowing the gap between the sexes. Nevertheless, the rate for men (73.0%) remains considerably higher than that of women (54.9%). Female employment rates are highest in the three Nordic countries, the United Kingdom and the Netherlands. Women still at a disadvantage in the labour market EU-wide, women are concentrated in the growing services sector (83% of all employed women against 58.9% of all employed men) whereas men are employed disproportionately in agriculture and industry, areas where more restructuring has taken place. Occupational segregation, by sector and occupation, may limit the choice of women entering or wishing to enter the labour market: women tend to be over-represented in low-paid sectors and occupations. Despite progress in recent years, women still have particular problems in gaining access to the labour market and particularly to managerial and supervisory positions (see also Women in politics 3.17): less than 6% of all women in employment occupy managerial posts compared with 10% of all men in employment. These developments notwithstanding, unemployment among women remains much higher than for men. While women form around 43% of the EU labour force, they account for half (50.4%) of the unemployed. The unemployment rate in 2001 was higher for women than men in most parts of the Union, averaging 8.6% as against 6.4%. (see also Unemployment 3.9). Employment rates for women remain systematically lower than for men. Moreover, many women work part-time. Female employees (14.6%) are also more likely than their male counterparts (12.4%) to have a fixed-term contract. Overall, mothers aged 25-49 with at least one young child (aged 0-5) are less likely (56.5%) to be employed than women of the same age without a young child (71%). The gap between these two groups is largest in Germany and the United Kingdom. In contrast, in Belgium and Portugal the two rates are almost identical. Differences between countries reflect, in particular, the extent of child-care provision, the availability of measures to reconcile work and family life, the availability of part-time work, the varying levels of taxation and welfare support. Gap between the sexes is narrowing but remains substantial One in three women in employment is working part-time The combination of increasing education and growth in the services sector, along with changing attitudes means that employment rates of women are converging on those of men. Between 1996 and 2001, they rose by almost 5 percentage points to 54.9%, whereas those for men increased only by 3 points to 73%. Although the difference is diminishing, it remains large in the vast majority of countries. In Sweden, the employment rate for women is 96% that of men although there has been a relative decline in women in work over the last few years. In virtually all Member States, the gap in employment rates between the sexes is smaller among the young generation than the older one. EU-wide, 33% of women in employment are working part-time against only 6% of men. Female part-time work is particularly prevalent in the Netherlands (71.3%) and the United Kingdom (44.1%). Among full-time employees, women work fewer hours than men in all Member States although in Austria and Sweden the difference is less than one hour. In contrast, the gender gap is more than 4 hours in the United Kingdom. Policy context ciple of equal treatment for men and women as regards access to employment, vocational training and promotion, and working conditions The EC Treaty (Article 137) states that "the Community shall support and complement the activities of the Member States in … equality between men and women with regard to labour market opportunities and treatment at work." Council Directive 93/104/EC of 23 November 1993 concerning certain aspects of the organisation of working time Directive 2002/73/EC of the European Parliament and of the Council of 23 September 2002 amending Council Directive 76/207/EEC on the implementation of the prin- Council Directive 96/34/EC of 3 June 1996 on the framework agreement on parental leave concluded by UNICE, CEEP and the ETUC 159 Section 3 Areas of social policy concern - Statistical portraits The reduction of gender gaps has been a priority since the start of the EES. And this area will remain a priority for the future of the EES. A continued increase of participation of women in the labour market is crucial for achieving the Lisbon targets on employment, particularly by encouraging older women to stay longer in the labour market and facilitating participation for mothers with small children. In order to increase employment growth and improve quality in work employment policies would need to focus on the structural inequalities of the labour market. These inequalities include gender gaps in employment, unemployment and non standard forms of employment; gender segregation in sectors and occupations; the gender pay gap. The under-representation of women in the key areas shaping the future knowledge based society, namely higher education and research has to be altered significantly. In addition it is important to promote more favourable conditions for women and men to enter, re-enter and remain in the labour market. Examples of these reconciliation policies include: adequate provision; access and quality of care services for children and other dependants; equal share of care and household responsibilities; an encouraged take-up of parental and other leave schemes by men, and possibilities for flexible work arrangements for both women and men. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on a community framework programme on gender equality (2001-2005). sion." The Stockholm summit in March 2001 set an intermediate target for female employment of 57% by 2005 and invited the Council and the Commission to develop indicators on the provision of care facilities for children and other dependants. The Barcelona European Council concluded that childcare should be provided to at least 90% of children between 3 years old and the mandatory school age and at least 33% of children under 3 years by 2010. One of the main objectives of the Social Policy Agenda (COM(2000) 379 final), Section 4.1.1.1 is to "realise Europe’s full employment potential by … increasing the number of women in work to more than 60% in 2010 whilst taking into account the different starting points of the Member States." It also stresses the need to give "more priority to equal opportunities." Methodological notes Source: Eurostat - Quarterly labour force data and European Union Labour Force Survey (LFS). For definition of activity (in the labour market), employment and unemployment rates and full-time/part-time, see Employment (3.7) and Unemployment (3.9). Because data about the labour status of all household members except the survey person are missing for Denmark, Ireland, Finland and Sweden, the comparison of employment by parental status is incomplete. Links to other parts of the report Communication from the Commission to the Council, the European Parliament, the Economic and Social Committee and the Committee of the Regions on "Employment and social policies: a framework for investing in quality” which establishes a set of indicators on quality in work and considers that "gender equality is a basic horizontal principle" (COM(2001) 313). Review of the implementation by the Member States and the European Institutions of the Beijing Platform for Action : Women in the decision making process, Council of the European Union, 11829/1/99. The Lisbon European Council in March 2000 concluded that "the employment rate is too low and is characterised by insufficient participation in the labour market by women … " (Presidency conclusion No.4). A female employment rate target was set at more than 60% by 2010. The Council also identified four key areas as part of an active employment policy. One of these areas was "furthering all aspects of equal opportunities, including reducing occupational segregation, and making it easier to reconcile working life and family life, in particular by setting a new benchmark for improved childcare provi- 160 Employment (3.7), Earnings of women and men (3.20), Labour market and Gender equality (Annexes II and IV). Further reading ● ● ● ● ● “European social statistics - Labour force survey results 2000”, 2001. Eurostat. “Employment in Europe 2002", September 2002. European Commission, Employment and Social Affairs DG. "Equal Opportunities for Women and Men in the European Union - Annual Report 1999". "Equal opportunities magazine", Quarterly Newsletter. European Commission, Employment and Social Affairs DG. Statistics in Focus (Population and social conditions): “Part-time work in the European Union”, No.13/1997. "Labour Force Survey Principal Results 2000", No.10/2001. Eurostat. Annual Report on Equal Opportunities for Women and Men in the European Union – 2001 – COM(2002)258 final. Areas of social policy concern - Statistical portraits Section 3 Key indicator EU 15 B DK D EL E F IRL I L NL A P FIN S UK 54.9 73.0 50.3 68.2 72.0 80.2 58.8 72.6 40.9 70.8 41.9 70.9 56.1 70.3 55.0 76.4 41.1 68.5 50.9 74.8 65.2 82.8 60.1 76.7 61.1 76.9 65.4 70.9 70.4 73.0 65.1 78.3 Employment rate. 15-64 years. 2001 Females Males Source: Eurostat - QLFD (Quarterly Labour Force Data) Graph 37 Female employment rates (15-64 years), 1996 and 2001 80,0 Graph 38 Percentage of persons in employment working part-time, by sex, 2001 80,0 % 80,0 1996 2001 60,0 60,0 40,0 40,0 20,0 20,0 0,0 0,0 EU-15 B DK D EL E F 80,0 % Male Female 70,0 IRL I L NL A P FIN S 70,0 60,0 60,0 50,0 50,0 40,0 40,0 30,0 30,0 20,0 20,0 10,0 10,0 0,0 UK 0,0 EU-15 B Source: Eurostat - QLFD (Quarterly Labour Force Data) DK D EL E F IRL I L NL A Source: Eurostat - QLFD (Quarterly Labour Force Data) 161 P FIN S UK Section 3 Areas of social policy concern - Statistical portraits 20 Earnings of women and men EU-wide, the average gross hourly earnings of women in 1999 were estimated at 16% less than the gross hourly earnings of men. The smallest differences are found in Portugal, Italy, Belgium and France, the biggest in the United Kingdom and Ireland. At EU level the difference remains the same as in 1998, 1997 and 1996. To reduce gender pay differences both direct pay-related discrimination and indirect discrimination related to labour market participation, occupational choice and career progression have to be addressed. Important pay differences between men and women persist in Europe, with women’s average gross hourly earnings around only 84% of men’s functions. This is a general feature in all Member States, with women least likely to be in supervisory functions relative to men in Italy, Greece and the Netherlands. According to the European Community Household Panel (ECHP), the average gross hourly earnings of women were 84% of men’s in 1999. Women’s earnings remain on average below those of men in all EU countries. Women’s average gross hourly earnings as a percentage of men’s vary from 78% in Ireland and 79% in the United Kingdom to 91% in Italy and 95% in Portugal. Women are furthermore often in non-standard employment such as fixed-term and part-time work. Compared to 6.2% of all employed men. For example, 33.4% of all women work in part-time. Men are thus not only more concentrated in higher paid sectors and occupations, but within these sectors and occupations they are also more likely than women to hold supervisory responsibilities and if they do so the earnings are relatively higher. The pay differences are related both to differences in the personal and job characteristics of men and women in employment and to differences in the remuneration of these characteristics Women and men in employment show important differences with respect to their personal and job characteristics, including labour market participation, employment, earnings, the sector and occupational employment structures as well as job status, job type and career progression. The differences in pay are particularly high among older workers (30%), the high-skilled (23%) and those employed with supervisory job status (19%). They also vary between different sectors of activity and different occupations, reaching 24% in the private sector in general, 28% in financial services, 25% in manufacturing as well as 31% among craft workers and 25% among plant and machine operators. Women have supervisory responsibilities much less frequently than men: 16% of men in paid employment in the EU had supervisory responsibilities and an additional 19% intermediate responsibilities in 1998 compared to less than 9% and 16%, respectively, of women. Men were overall twice as likely to occupy such supervisory Policy context Furthermore, while both men and women have lower earnings in female-dominated sectors and occupations, this wage penalty is more pronounced for women. Finally, independently of the initial pay differential the gender pay differential widens considerably throughout working life. Both the above differences in the composition of the male and female workforce and differences in the remuneration of the personal and job characteristics between men and women contribute to the overall gender differences in pay. As shown in Employment in Europe 2002, in particular differences in the male and female workforce composition related to the sector of employment and the occupational category contribute significantly to the gender differences in pay. Since such compositional differences can be due to various forms of indirect discrimination such as traditions and social norms and constraints on choices related to education, labour market participation, occupation and career progression both types of gender differences and both forms of potential discrimination - direct pay-related one and indirect one related to the above choices – have to be addressed to reduce the differences in pay. The important gender differences which persist in the European labour markets need to be tackled to promote economic growth, employment and social cohesion. ‘pay’ means the ordinary basic or minimum wage or salary and any other consideration, whether in cash or in kind, which the worker receives directly or indirectly, in respect of his employment, from his employer. Equal pay without discrimination based on sex means: The EC Treaty (Article 141) states that "Each Member State shall ensure that the principle of equal pay for male and female workers for equal work or work of equal value is applied. For the purpose of this Article, (a) that pay for the same work at piece rates shall be calculated on the basis of the same unit of measurement; (b) that pay for work at time rates shall be the same for the same job. 162 Areas of social policy concern - Statistical portraits Section 3 Council Directive 75/117/EEC of 10 February 1975 on the approximation of the laws of the Member States relating to the application of the principle of equal pay for men and women. Statistics based on the Structure of Earnings Survey (SES) from 1995 exclude people who are self-employed or who work in local units employing less than ten people, and also employees in agriculture and fishing, public administration and defence, education, health and social work, other community, social and personal service activities, private households or extra-territorial organisations. The coverage of this survey is not ideal to study women’s earnings because sectors where there are a majority of women are thus not covered: health, education and personal services. The earnings differences between genders are probably slightly less important in these categories but at the same time the average earnings are lower which in turn would lower women’s overall averages. The 2000 Employment Guidelines (No.19): “They (Member States) will initiate positive steps to promote equal pay for equal work or work of equal value and to diminish differentials in incomes between women and men.” The 2001 Employment Guidelines further specified that actions are needed to address gender differences in pay in both the private and public sectors and that the impact of policies on gender differences in pay should be identified and addressed. The 2002 Employment Guidelines also asked to set targets to tackle the differences in pay and to include in the strategy, inter alia, a review of job classification and pay systems to eliminate gender bias, improving statistical and monitoring systems, and awareness-raising and transparency as regards differences in pay. Links to other parts of the report Employment of women and men (3.19), Labour market and Gender equality (Annexes II and IV) Communication from the Commission to the Council, the European Parliament, the Economic and Social Committee and the Committee of the Regions on "Employment and social policies: a framework for investing in quality” Further reading The Employment Committee Report on Indicators of Quality in Work contains indicators on earnings under the form of transition tables. ● ● ● Methodological notes Sources: Eurostat – European Community Household Panel (ECHP) Users’ Data Base version of December 2002 (except France, the Netherlands and Sweden ; France: National Labour Force Survey, the Netherlands and Sweden: Earnings Surveys.) ● ● The EU-15 figure is a weighted average of national values estimated without missing countries. ● The gender pay gap is not adjusted for age, occupation and sector. In May 2002, the ECHP Working Group concluded that an adjusted gender pay gap cannot be calculated on the basis of the ECHP. It further agreed that econometric studies of the factors related to the gender pay gap on the basis of the ECHP should be continued. ● The ECHP will be replaced in 2003 with a new instrument, EU-SILC (Statistics on Income and Living Conditions). Econometric analyses of the gender pay gap on the basis of this new data set, however, will be difficult due to the separation of cross-sectional and longitudinal information as well as due to the lack of information on the occupational employment structure, the characteristics of small jobs and gross earnings. ● ● ● ● 163 “Employment in Europe 2002", section "Assessing gender pay gaps in the EU", September 2002. European Commission, Employment and Social Affairs DG. Panorama of the European Union (Population and social conditions): “The life of women and men in Europe. A statistical portrait”. Eurostat 2002. OECD Employment Outlook 2002 - Chapter 2 "Women at Work: Who are They and How are They Faring?" “Earnings in industry and services - Hours of work in industry, 1996-1998", 2000 edition. Eurostat. Statistics in Focus (Population and social conditions): “Earnings of men and women in the EU: the gap narrowing but only slowly”, No. 5/2001 and “Women’s earnings in the E.U: 28% less than men’s”, No. 6/1999. Eurostat. European Parliament: - Resolution and report on equal pay for work of equal value “Industrial Relations in Europe", 2000. European Commission, Employment and Social Affairs DG. Indicators on gender pay equality: The Belgian presidency’s report, 2001. "The adjusted gender pay gap: a critical appraisal of the standard decomposition techniques". Network of experts on employment and equality between women and men, DG Employment and Social Affairs. The gender pay gap and the gender mainstreaming pay policy: synthesis report of the gender pay equality in EU Member States. Network of experts on employment and equality between women and men, DG Employment and Social Affairs. Annual Report on Equal Opportunities for Women and men in the European Union – 2001COM(2002)258 Section 3 Areas of social policy concern - Statistical portraits Key indicator EU-15 B DK D EL E F IRL I L NL A P FIN S UK 79 79 78 77 77 77 79 79 78 80 78 : 95 94 93 94 95 90 81 81 82 83 : : 83 82 83 83 85 84 78 76 79 76 74 72 Gender pay gap in unadjusted form (Average gross hourly earnings of females as % of average gross hourly earnings of males. The population consists of all paid employees aged 16-64 that are 'at work 15+ hours per week'). 84* 84* 84* 84* 83* 84* 1999 1998 1997 1996 1995 1994 89 91 90 90 88 87 86 88 87 85 85 89 81 78 79 79 79 79 87 88 87 85 83 87 86* 84* 86* 86* 87* 90 88 88 88 87 87 87 78 80 81 79 80 81 91 93 93 92 92 92 : : : 82 81 83 Source: Eurostat - European Community Household Panel UDB version December 2002 (except F: National Labour Force Survey, NL and S: Earnings Surveys.) Graph 39 Gender pay gap in unadjusted form 1998 and 1999 1998 Graph 40 Average gross annual earnings of females as % of average gross annual earnings of males (full-time employees, NACE Rev. 1 sections C-K), 1999 and 2000 1999 100 100 100 100 80 80 80 80 60 60 60 60 40 40 40 40 20 20 20 20 EU-15 B DK D EL E F IRL I L NL A P FIN S 0 0 0 0 1999 2000 EU 15 B UK DK D EL E F IRL I L NL Source: Eurostat - Harmonised statistics on earnings Source: Eurostat - European Community Household Panel UDB version December 2002 (except F: National Labour Force Survey, NL and S: Earnings Surveys.) 164 A P FIN S UK Areas of social policy concern - Statistical portraits Section 3 21 Life and health expectancies Life expectancy continues to rise and now it's more than 81 years for women and 75 for men. In all Member States, women live longer than men. EU-wide, women can expect to live to 66 and men to 63 years of age without any disability. Average life span continues to increase rage, only 6% of people with tertiary education described their health as '(very) bad' compared with 16% of those with compulsory education at best. Over the past 50 years, life expectancy of men and women has risen steadily: by around 10 years in total for each sex. Throughout the Union, women live longer than men. In 2000, the life expectancy of women in EU15 was 81.4 years while that for men was 75.3 years. Eurostat estimates that the life expectancy of women and men may reach 84 and 78 years respectively by the year 2020. 52% of the EU population aged 65 and over report being hampered in their daily activities by a chronic, physical or mental health problem, illness or disability (29% are "severely" hampered, 37% "to some extent"). Around six milion Europeans are affected by dementia Women can expect to live to 66 years and men to 63 years without any disability Dementia is one of the most important causes of disability in the elderly. With the increasing proportion of the elderly in many populations, the number of dementia patients will rise also. The most common causes of dementia in EU are Alzheimer’s disease (about 50-70% of cases) and the successive strokes which lead to multiinfarct dementia (about 30%). An estimated number of 5.65 million Europeans between 30 and 99 years of age suffered from different types of dementias in 2000 (12.3 per 1000 inhabitants). Within this group, more women (3.5 million) than men (2.1 million) are affected. Sweden (14.9) and Italy (13.9) show the highest estimated prevalence, and Portugal (10.4) and Ireland (8.4) the lowest. This leads to a increasing pressure on the longterm systems of healthcare. Health expectancies are a group of health indicators combining data on mortality and disability/morbidity. This report uses life expectancy without (severe) disability. At EU-level, women can expect to live to 66 years of age without any disability and men 63. People suffering from a severe disability have low life expectancies, e.g. women at 16 years of age with severe disability can expect to live 5 years. The corresponding figure for men is 4 years. Large reduction in infant mortality Progress in medical research and care has also led to a dramatic improvement in the infant mortality rate for EU-15 which has fallen from 23 deaths per 1000 live births in 1970 to less than 5 deaths per 1000 live births in 2000. Differences between Member States have virtually disappeared. Circulatory diseases and cancer remain the major causes of death Mortality patterns differ significantly according to age and sex. As a general rule, mortality is higher among men than women in all age groups. For both men and women, circulatory diseases are the major cause of death throughout the Union (the one exception is in France where men are most likely to die of cancer): 700,000 men and 850,000 women died of such diseases in 1999. For men, this represents 325 and 248 deaths per 100,000 population, and for women 207 and 139. External causes of injury and poisoning prevail among the young (aged 15-34) but account for only a small proportion of those aged 55 and over. Cancer represents the major cause of death among those aged 45-64. For those aged 75 and over, circulatory diseases account for around half of all deaths. Almost one in four elderly people describe their health as 'bad' EU-wide, around 12% of adults (aged 16 and over) perceive their health to be 'bad' or 'very bad' in 1998. 60% feel that their health is 'good' or 'very good' while the remaining 28% describe it as 'fair’. Women were slightly more likely than men to describe their health as fair, bad or very bad – 43.3% compared to 36.1%. Generally speaking, the likelihood of self-perceived health as very good or good decreases as age increases. After a plateau of 85.3% for those aged 16 to 24, a drop to 78.6% was found in the 25 to 34 age group. With each successive age group after that, very good or good self-rated health declined, reaching a low of 23.7% for the EU population aged 85 or older. This pattern can be observed in every Member State with one or two minor exceptions. 10% of the EU adult population is hospitalised every year In 1998, 10.1% of Europeans had experienced a hospitalisation during the last 12 months (9.1% of men and 11.0% of women). The proportion ranges from 5.9% in Portugal and in Greece, to 14.2% in Austria and People with a high level of education report better health than those with a low level of education. On ave- 165 Section 3 Areas of social policy concern - Statistical portraits 12.1% in Germany. These differences may partly reflect the differences in organisation of healthcare services. The proportion rises to more than 20% among the 'very old'. Older men are more likely than women to be hospitalised. In terms of frequency of admission, (discharges from hospitals) following the ICD (International Classification of Diseases), diseases of the circulatory system (2,420 per 100,000) comprise the highest frequency of admission followed by admissions for cancer (1,367), traumas and poisoning (1,646) and respiratory diseases (1,427). The incidence is not so high for mental disorders (655) and infectious diseases (394). and private hospitals, but they differ with respect to the inclusion of nursing homes and day care beds. A further reason is the financial constraints which arose during the 1990s and which have led to a rationalisation of healthcare services everywhere. The increased demand for healthcare for elderly people, many of whom are suffering from chronic disability and diseases, has in most cases been met by transferring beds for acute or psychiatric care to longterm care, while total numbers are still declining. The supply of hospital services at national and regional levels is, however, very closely linked to total healthcare expenditure. The number of hospital beds decreases sharply Health expenditure accounts for 8% of EU GDP The total number of hospital beds has decreased substantially in the EU since 1990. For EU-15, it decreased 17% between 1990 and 2000. A considerable share of this reduction is likely to have been caused by the drop in the length of hospital stay. It decreased in EU-15 from 17.4 days in 1980 to less than 11 days in 1999. Spain and UK have the lowest number of beds per 100,000 in all Member States — 413 in 1999 — and Germany has the highest with 920. All these numbers refer to both public Policy context The EC Treaty (Title XIII Public Health, Article 152) states that "Community action, which shall complement national policies, shall be directed towards improving public health, preventing human illness and diseases, and obviating sources of danger to human health. Such action shall cover the fight against the major health scourges, by promoting research into their causes, their transmission and their prevention, as well as health information and education." Article 1 of the Community Action on health monitoring (Decision No 1400/97/EC of the European Parliament and of the Council of 30 June 1997) states: "The objective of the programme shall be to contribute to the establishment of a Community health monitoring system which makes it possible to a) measure health status, trends and determinants throughout the Community …" The Laeken European Council (2001) called for the development an approach in the field of healthcare and care for the elderly similar to the one being developed for the pensions. The long-term objectives presented in the Communication of the Commission (COM (2001) 723) are: accessibility, quality and financial viability of health and care systems. Particular attention will have to be given to the impact of European integration on Member States' healthcare systems. The new Programme of Community action in the field of public health (2003-2008), adopted by Decision of the European Parliament and of the Council stresses the 166 In 2000, total EU expenditure on health represented 8.0% of EU GDP. Germany (10.3%) and France (9.5%) spend the most although they are still well behind the US (13.0%). Over the last decade or so, health expenditure as a percentage of GDP rose in the majority of countries. The most significant increases were observed in Belgium, Germany and Portugal. The only countries showing a decrease are Sweden and Luxembourg. importance of development and dissemination to competent authorities in Member States, to health and other professionals and, where appropriate, to other stakeholders and the general public of health information and knowledge, including statistics, reports, reviews, analysis, and advice on issues of common interest to the Community and to Member States. Methodological notes The infant mortality rate is defined as the number of infants who die within the first year of life divided by the number of live births (per 1000 live births). Life expectancy at birth is the average number of years a person would live if age-specific mortality rates observed for a certain calendar year or period were to continue. Life expectancy without disability is calculated by the Sullivan method and uses the mortality data and disability prevalence figures from the ECHP. To be able to present calculations at birth, Eurostat has, for all countries and for both genders, applied a constant disability rate (of 1%) between the ages 0 and 16. The life expectancy without disability figures concerning the year 1994 which were published last year in this report, are not directly comparable to the figures in this report (concerning the year 1996). Data on perceived health are based on a subjective question addressed to private households in the ECHP. For the total population (particularly aged 65 and over), the percentages on (very) bad health may be somewhat higher due to the fact that a significant number of people live in homes or institutions for long-term nursing care. The study on dementia cases by Alzheimer Europe was based solely on diagnosed cases. This poses a problem in accurately estimating Areas of social policy concern - Statistical portraits Section 3 the number of people with dementia, as many people with dementia never receive a diagnosis and it excludes those in the early stages of dementia who have not yet been diagnosed. Data on the number of beds reported to Eurostat are normally given as an annual average of beds in use during the year of reporting or according to concepts of registration or budgetary or planned approval. The data must be treated with caution due to the different concepts of ‘hospital’ and ‘hospital bed’ in the EU countries Further reading ● ● ● ● ● Links to other parts of the report ● Ageing in the population (3.3), Health and safety (Annexes II and IV) ● “Health statistics: Key data on Health 2002", 2002 edition. Eurostat. “Health statistics: Atlas of Mortality", 2002 edition. Eurostat. Eurostat - Demographic Statistics and European Community Household Panel (ECHP) UDB version September 2001. OECD Health data 2002. “European social statistics - Demography”, 2001 edition. Eurostat. The future of healthcare and care for the elderly: guaranteeing accessibility, quality and financial viability - COM (2001) 723 Adapting to change in work and society: a new Community strategy on health and safety at work 2002–2006 – COM(2002) 118 Key indicator EU-15 B DK D EL E F IRL I L NL A P FIN S UK 75.3 81.4 74.6 80.8 74.5 79.3 74.7 80.7 75.5 80.6 75.5 82.7 75.2 82.7 74.2 79.2 76.3 82.4 74.9 81.3 75.5 80.5 75.4 81.2 72.7 79.7 74.2 81.0 77.4 82.0 75.4 80.2 67 70 65 68 60 63 64 67 67 70 61 64 63 63 62 66 59 61 56 59 : : 61 62 Life expectancy at birth. 2000 Males Females Note: D. EL: 1999. Source: Eurostat - Demographic statistics Healthy life years (Disability-free life expectancy at birth), 1996 63 66 Males Females 65 69 62 62 63 69 Source: Eurostat - Mortality Statistics and European Community Household Panel Graph 41 Major causes of death by age-group, EU-15, 1998 100 % Graph 42 Percentage of population hospitalised during the last 12 months, 1998 100 90 90 80 80 70 18 12 60 50 40 40 8 30 30 6 20 20 10 10 15-24 25-34 35-44 45-54 Other External causes of injury and poisoning 55-64 65-74 75-84 85+ 15,6 11,0 11,8 10,8 14 12,6 12,1 11,6 10,6 9,6 12 8,8 8,3 10 8,7 8,4 8 6,1 5,8 6,5 6,1 5,7 6 4 4 2 2 0 Cancer Circulatory diseases 12,3 11,0 9,5 8,6 8,1 8,3 0 16 13,5 10 9,1 50 0 18 Male Female 14 70 60 % 16 EU-15 B DK D EL E F IRL I L NL A P FIN S Source: Eurostat - European Community Household Panel UDB, version December 2001 Source: Eurostat - Mortality Statistics 167 UK 0 Section 3 Areas of social policy concern - Statistical portraits 22 Accidents and work-related health problems In 2000, around 4.0% of EU workers were victims of a working accident resulting in more than three days' absence, 6.3% including accidents with no absence from work or an absence of up to 3 days. From 1994, the number of accidents at work with more than three days' absence decreased by 11% (the value of the index 1998 = 100 was 99 in 2000 and 111 in 1994). During 199899 5.4% of employees per year suffered from work-related health problems. A total of around 510 million working days were lost in 1999 as a result of accidents at work (160 million days lost) and work-related health problems (350 million days lost). Road transport fatalities have fallen by around 46% since 1970 but there were still around 40 000 deaths on EU roads recorded in 2001. Working accidents more frequent among younger and low seniority workers In 2000, around 4.8 million accidents at work - that resulted in more than three days’ absence - were recorded in the Union. Including the accidents with no absence from work or an absence of up to three days, the estimated total number of accidents at work in the EU is 7.7 million in 2000. This represents respectively estimated rates of 4,037 and 6,299 accidents at work per 100,000 employed people, or put another way, 6.3% of all workers were the victims of an accident at work during the year (4.0% for accidents with an absence of more than 3 days). There was a substantial drop in this rate (accidents resulting in more than three days absence) of 11.1% between 1994 and 2000 (index = 99 in 2000 and 111 in 1994) but there was a relative stability from 1997 (rates of 4,106, 4,089 and 4,088 for accidents with more than three days’ absence in 1997, 1998 and 1999 respectively). In addition, 5,275 fatal accidents in the course of work were recorded in 1999 in EU-15, of which 41% were road traffic or transport accidents during work. For 2000, the provisional total number is 5,052 and the provisional incidence rate is 4.4 fatalities per 100,000 employed people against 6.1 in 1994 and 4.8 in 1999 (-28% and -8% respectively). These proportions differ of course on the economic activity and the size of the enterprise, as well as the age, sex and working conditions of the workers. The construction industry has the highest incidence of accidents resulting in more than three days absence, though decreasing since 1994: 7,579 per 100,000 workers in 2000 against 9,014 in 1994. Agriculture has the second highest incidence: 6,669 in 2000 (6,496 in 1994). For fatal accidents, agriculture has the highest incidence and construction the second highest one: respectively around 12.4 and 11.1 per 100,000 workers in 2000. When including accidents up to three days absence (1998-1999 data from the ad hoc module in the European Union Labour Force Survey), the accident rate is particularly high in the fishing industry (where the risk of an accident is 2.4 times greater than the average for all branches in the EU), in agriculture, construction and 168 health and social work (1.3 to 1.4 times). In the local units of manufacturing, construction, wholesale and retail repairs, hotels and restaurants and transport employing between 10 and 49 people, the risk is 1.2 to 1.5 times greater than the average for these branches in 1999 (more than three days absence). For all branches together, the mean risk in 10 to 49 people local units is close to 1.3 times the average. The risk is also high in local units that employ 1 to 9 people in the manufacturing and construction industries (respectively 1.7 and 1.2 times the average for each branch in 1999), and in local units employing 50 to 249 people in wholesale and retail repairs, hotels and restaurants and transport (1.3 to 1.4 times in 1999). With the exception of Greece, Ireland and Portugal, the incidence of accidents decreases with age in all Member States. In contrast, the incidence of fatal accidents tends to increase considerably with age. Men are around three times more likely than women to have an accident - resulting in more than three days absence - and about ten times more likely to have a fatal accident. This result is a function of men’s jobs and sectors of activity which tend to be more highrisk than those of women. There are also relatively more women who work part-time which may reduce their exposure to risk. Finally, people who have been working for less than 2 years in a business, shift workers, night workers or people working fewer than 20 hours per week are also 20% to 50% more likely than average to have an accident. Accidents at work: 157 million working days lost to the economy In addition to the major impact of these accidents in human terms, they also have a high socio-economic cost: in 1999, though for 37% of accidents there was no absence from work or the resulting absence was only up to three days, for 29% the absence was more than three days but less than two weeks and for 30% the absence was between two weeks and three months. For the remaining 4% of accidents, the consequence was an absence of three months or more, or permanent partial or total disability. It is estimated that 157 million work days were lost in 1999 in the EU owing to accidents at Areas of social policy concern - Statistical portraits Section 3 work, i.e. a mean of 21 days per accident (32 days per accident with more than three days absence) and the equivalent of one day of work lost per year for every person in employment. Additionally, 5% of the victims had to change to a different type of work or another job, or to reduce working hours. Finally, about 14% of the victims of accidents at work suffer more than one accident per year. EU roads claimed around 40 000 lives in 2001 For the EU as a whole, road transport fatalities have been in constant decline, showing an approximate 46% decrease compared with 1970 despite the fact that road transport more than doubled over the same period. The biggest improvements (reductions of 60% or more) were recorded in Germany, Netherlands and Finland. This general downward trend since the early 1970s has not been apparent in Greece, Portugal and to a lesser extent Spain, where car ownership has grown rapidly and road fatalities remain at a very high level. From 1991 to 2001 the fatalities have decreased in all Member States totalling to a 30% decrease for EU-15. The biggest decreases have been recorded in Austria and Germany (both 38%), the smallest in Ireland (8%) and Greece (11%). 350 million working days lost due to work-related health problems On the basis of the results available for 11 Member States from the European Union Labour Force Survey (self-assessment by survey respondents of their workrelated state of health), it is estimated that during the period 1998 to 1999 each year almost eight million people in work or having been in work in the EU were suffering from health disorders, other than accidental injuries, caused or aggravated by their current or past employment. The prevalence rate for employees is 5,372 cases per 100,000 people per year (7,150 for 55-64 yearolds) linked to their current employment. Up to 53% of cases involve musculoskeletal disorders, which are more frequent in the construction, transport and health and social work sectors (prevalence in these sectors is 1.2 to 1.6 times higher than average). Stress, depression and anxiety represent 18% of the problems, and 26% of those involving two or more weeks absence from work (this rate doubles in education and health and social work). Finally, pulmonary disorders affect yearly 0.6 million people (the risk doubles in the mining industries). From 1998 to 1999, an estimated 350 million working days were lost each year in the EU owing to workrelated health problems. In spite of the general improvement in road safety, the estimated number of deaths caused by road traffic accidents in 2001 was around 40,000 for EU-15. Whatever the indicator used (number of deaths related to the population or to the total number of cars), Greece and Portugal record the worst levels of road safety. While for the Union as a whole around 104 people per million population died on the roads, the corresponding rates for Portugal and Greece were 184 and 178 respectively. The United Kingdom and Sweden have the lowest death rate (60 and 63 respectively) followed by the Netherlands (66) and Denmark (77). Rail transport resulted in relatively few fatalities, with a clear advantage, in safety, over road transport. Home and leisure accidents There were an estimated 430,000 home and leisure accidents in the EU in 1995 (men had 240,000, women 190,000). Accidents are most likely to occur at home (32% of the total number of accidents among men, 46% among women) followed by sporting accidents (18% among men, 10% among women). The first results of the Third European Survey on Working Conditions, carried out by the European Foundation for the Improvement of Living and Working Conditions in 2000 reveal that problems related to health, the pace of work and working time continue to rise in European workplaces. The percentage of workers exposed to intense noise, painful/tiring positions and handling of heavy goods continues to increase and the pace of work has quickened. Large numbers of workers complain of stress and burnout. Almost 600,000 commuting accidents in the Union The number of commuting accidents (accidents on the way to and from work) in the Union resulting in more than three days’ absence was estimated at approximately 580 000 in 1998 (in addition to accidents at work). The incidence rate was 410 per 100 000. The number of fatal commuting accidents, which were chiefly road traffic and transport accidents, was around 3 100 for the entire EU. 169 Section 3 Areas of social policy concern - Statistical portraits Policy context The EC Treaty (Article 137) states that "the Community shall support and complement the activities of the Member States in … (the) improvement in particular of the working environment to protect workers’ health and safety." Art.140 adds that "the Commission shall encourage cooperation between the Member States and facilitate the coordination of their action in all social policy fields under this chapter, particularly in matters relating to … (the) prevention of occupational accidents and diseases". On 29 April 1999, the European Economic and Social Committee of the EU gave an opinion on "Health and Safety in the workplace - Application of Community measures and new risks" (O.J. C 51 of 23.02.2000, p33). It looks at changes occurring in work organisation systems and the associated occupational risks such as the increase in psychosocial complaints and burnout. The Commission adopted on 17 March 2000 a Communication (COM(2000)125 final) on "Priorities in EU road safety: Progress report and ranking of actions." It encourages Member States, regional and local authorities to "establish a practice of calculating the costs and effects of road safety measures and where appropriate comparing these with the costs of avoided accidents" and invites them "to increase investment in road safety projects …" On 20.6.2001 the Commission gave the Communication on “Employment and social policies: a framework for investing in quality”. It takes forward the Social Policy Agenda commitment and the Lisbon strategy reinforced by Nice and Stockholm, to promote quality in employment. In particular it defines the approach of improving quality of work and ensures its integration in employment and social policies. For this purpose it establishes a set of indicators on quality in work to be used within the framework of the European Employment Strategy. The lists of indicators of both the Synthesis Report and the Employment Committee Report on Indicators of Quality in Work include the evolution of the incidence rate of accidents at work, as defined by the number of accidents at work per 100,000 people in employment. In the future a composite indicator covering accidents and occupational diseases including as a result of stress will be developed by the Commission. More recently, on 11.03.2002, the Commission adopted a Communication (COM(2002) 118 final) on “Adapting to change in work and society: a new Community strategy on health and safety at work 2002–2006” and on 03.06.2002 the Council adopted a Resolution on “a new Community strategy on health and safety at work 170 (2002–2006)”. The Resolution stated as ones of the main objectives: “reducing the number of occupational accidents and illnesses. For this purpose, quantified objectives should be set, which presupposes stepping up the work in progress on harmonising statistics on accidents at work and occupational illnesses”, “placing more emphasis on the prevention of occupational illnesses”, “taking into account social risks such as stress and harassment at work, as well as the risks associated with dependence on alcohol, drugs and medicines”, “promote a prevention culture right from the earliest stages of education and provide continuing vocational training” and “integrate health and safety at work into business management”. Methodological notes Sources: Eurostat - European Statistics on Accidents at Work (ESAW), ad hoc module on accidents at work and occupational diseases in the 1999 Labour Force Survey and Transport Statistics. European Commission Transport DG - Community Road Accident database (CARE). European Home and Leisure Accident Surveillance System (EHLASS). For road accidents, people killed are all those killed within 30 days of the accident. For Member States not using this definition, corrective factors were applied. The data on working accidents relate to almost 90% of people in employment in the Union. Only those working accidents that lead to more than three days absence are included in the annual data source (ESAW) but accidents with no absence from work or resulting in an absence from work from one to three days were also covered in the ad hoc module on accidents at work and occupational diseases in the 1999 Labour Force Survey. The ESAW incidence rates have been calculated for only nine major branches of economic activity (NACE Rev. 1 sections). The third European Survey on Working Conditions was carried out in 2000 by the European Foundation for the Improvement of Living and Working Conditions. The previous surveys were carried out in 1990 and 1996. The EHLASS (European Home and Leisure Accident Surveillance System) was introduced by the Council Decision 93/683/EEC of 29 October 1993 introducing a Community system of information on home and leisure. Since 1999 the EHLASS system has been integrated into the Community Programme of Prevention of Injuries. Links to other parts of the report Health and safety (Annexes II and IV). Areas of social policy concern - Statistical portraits Section 3 Further reading ● ● ● “European social statistics – Accidents at work and work-related health problems – Data 1994-2000” – Detailed tables series - 2002 edition - Eurostat. Statistics in Focus (Population and social conditions): “Accidents at work in the EU in 1998-1999”, No.16/2001 and “Work-related health problems in the EU 1998-99”, No 17/2001; Statistics in Focus (Population and social conditions): “The health and safety of men and women at work”, No. 4/2002; Eurostat. Statistics in Focus (Transport): "Transport Safety", No 3/2000; Eurostat. Statistics in Focus (General statistics): “Road-traffic deaths in the regions of Europe”, No 5/2001; Eurostat. ● ● ● ● “European Statistics on Accidents at Work Methodology", 2001 Edition. Eurostat and DG Employment and social affairs, “Health and safety at work” series. “Key data on Health", 2000 edition. Eurostat. “Panorama of transport” (2001 edition), 2002. Eurostat. “Third European Survey on Working Conditions", 2000. "Precarious Employment and Health-Related Outcomes in the European Union", 1999. “For a better quality of work”, September 2001. European Foundation for the Improvement of Living and Working Conditions. “Guidance on work-related stress - Spice of life or kiss of death?", European Commission, 16 December 2002. Key indicator EU-15 B DK D EL E F IRL I L NL A P FIN S UK 105 : : 92 92 93 94* 96* 93* 89 89 88 111 113 106 111 109 118 115 100 79* 88 85 88 Serious accidents at work (Index of the number of serious accidents at work per 100,000 persons in employment (1998=100)), 2000. Total Men Women 99* 82~b 98* 80~b 104* 101 89 88 99 96 96 99 88 92 76 108 109 113 102 101 111 72 69 88 99 98 104 104 105 100 Fatal accidents at work (Index of the number of fatal accidents at work per 100,000 persons in employment (1998=100)), 2000. Total 79* 100 61 70 73 85 85 39 66 149* Source: Eurostat - European Statistics on Accidents at Work (ESAW) Graph 43 Accidents at work by type of activity, EU-15, 2000 Graph 44 Number of road traffic deaths per million population, 2001 per 100 000 employed persons 0 2000 4000 6000 8000 10000 0 12000 9810 Fishing (estimated) 7579 Construction 6669 Agriculture. hunting and forestry Transport. storage and communication 5457 Health and social work (estimated) 5410 Manufacturing 4450 Hotels and restaurants 3821 Wholesale and retail trade; repairs 2552 0 2000 4000 6000 8000 10000 20 40 UK S NL DK FIN D EU-15 IRL I A E F B L EL P Source: Eurostat - European Statistics on Accidents at Work (ESAW) 80 100 120 140 160 180 160 180 200 60 63 66 77 84 85 104 106 111 117 129 137 143 144 178 184 0 12000 60 20 40 60 80 100 120 140 200 Source: CARE (Community Road Accident Database) and Eurostat - Demographic Statistics.Notes: B, I and UK: 2000 data from national sources. All 2001 data are estimates. 171 Annexes Annex I Key social indicators per Member State Annex II Statistical data – European Union Member States Annex III Key social indicators per acceding State and candidate country Annex IV Statistical data – European Union acceding States and candidate countries Annex V Symbols, countries and county groupings, other abbreviations and acronyms Annex VI Eurostat Data Shops 173 Annex I Annex I: Key social indicators per Member State Nr. 3 4 Key indicator Unit Year EU-15 B DK Old age dependency ratio Net migration rate % 2001 per 1000 inhab. 2001 24.3° 25.7 22.2 3.1 3.2 2.3 3.2 19.4 13.6 16.8 21.9 15.0 16.8 8.4 7.9 8.9 12.3 7.3 7.7 6.9 64.0 Early school-leavers not in further education or training - total % 2001 5m Early school-leavers not in further education or training - males % 2001 5f Early school-leavers not in further education or training - females % 2001 6t Lifelong learning - total % 2001 6m Lifelong learning - males % 2001 6f Lifelong learning - females % 2001 7 Employment rate (cf. nrs 19m & 19f) % 2001 8at Employment rate of older workers - total % 2001 8am Employment rate of older workers - males % 2001 8af Employment rate of older workers - females % 2001 8bt Effective average exit age - total years 2001 8bm Effective average exit age - males years 2001 8bf Effective average exit age - females years 2001 9t Unemployment rate - total % 2001 9m Unemployment rate - males % 2001 9f Unemployment rate - females % 2001 10 Youth unemployment/population ratio % 2001 11t Long-term unemployment rate - total % 2001 11m Long-term unemployment rate - males % 2001 11f Long-term unemployment rate - females % 2001 12 Social protection expenditure as a percentage of GDP % 2000 13 Old age and survivors benefits as a percentage of total social benefits % 2000 14 Active public expenditure in LMP as a percentage of GDP % 2000 15 Inequality of income distribution Ratio 1998 16a Risk-of-poverty rate before social transfers % 1998 16b Risk-of-poverty rate after social transfers % 1998 17 Population in jobless households % 2000 18 Female share in national Parliaments % 2001 19m Employment rate - males (cf. nr. 7) % 2001 19f Employment rate - females (cf. nr. 7) % 2001 20 Gender pay gap in unadjusted form % 1999 21am Life expectancy at birth - males Years 2000 21af Life expectancy at birth - females Years 2000 21bmHealthy life years - males Years 1996 21bf Healthy life years - females Years 1996 22at Serious accidents at work - total Index points (1998 = 100) 2000 22am Serious accidents at work - males Index points (1998 = 100) 2000 22af Serious accidents at work - females Index points (1998 = 100) 2000 22b Fatal accidents at work Index points (1998 = 100) 2000 D EL E F IRL I L 24.5 25.6° 24.7 24.8 16.6 27.1 21.5 5.8 1.0 7.8 2.9 7.5 12.5 16.5 28.6 13.5 18.9 26.4 16.9 12.2 20.4 34.9 15.0 22.6 16.7 17.8 16.4 19.1 12.8 5.2 5.7 4.8 13.0 22.2 1.4 4.9 1.5 4.3 1.2 5.5 12.0 2.7 2.5 3.0 15.1 5.2 5.2 5.3 59.3 76.2 65.8 55.4 56.3 63.1 38.6 26.5 58.0 37.7 38.0 38.9 48.7 36.5 65.5 46.1 55.0 57.4 28.9 59.9 60.5 16.9 57.0 57.8 49.8 61.9 62.2 29.5 60.7 60.9 59.1 7.4 6.4 8.5 55.9 6.6 6.0 7.4 61.1 4.3 3.8 4.9 7.3 5.8 3.2 2.8 NL A P FIN 20.1 22.9 S UK 24.2 22.4 2.2 6.3 1.2 3.2 2.6 18.1 15.3 10.2 45.2 10.3 10.5 : 30.2 19.0 16.5 9.7 52.3 13.0 11.3 : 22.6 5.1 4.9 5.2 17.2 5.3 5.9 4.7 14.1 10.7 16.3 8.2 17.0 8.7 15.5 7.7 38.0 3.3 3.0 3.7 7.7 19.3 17.1 21.4 9.7 17.5 15.4 19.7 : 21.7 18.0 25.7 65.7 54.8 62.9 74.1 68.4 68.8 68.1 71.7 71.7 31.0 46.8 28.0 24.4 39.6 28.6 50.3 45.7 66.5 52.3 35.4 64.7 40.4 34.8 51.1 40.0 61.6 46.7 69.1 61.7 22.5 21.8 59.6 60.6 61.2 60.7 26.7 58.1 58.2 28.8 63.1 63.2 16.2 59.4 59.6 14.0 56.8 57.5 28.0 17.9 60.9 59.6 61.1 60.0 40.6 62.0 62.0 44.8 61.6 61.6 63.8 62.0 62.1 43.1 62.1 63.1 60.4 7.7 7.7 7.8 57.7 60.2 10.5 10.6 7.0 7.5 15.6 15.4 58.0 8.6 7.0 10.3 62.2 3.8 3.9 3.7 59.2 9.4 7.3 12.9 55.3 2.0 1.7 2.4 60.3 58.6 2.4 3.6 1.9 3.0 3.0 4.3 61.5 4.1 3.2 5.1 61.4 9.1 8.6 9.7 61.9 4.9 5.2 4.5 61.0 5.0 5.5 4.4 5.9 4.7 10.2 10.8 6.9 3.3 10.2 2.5 4.5 10.3 5.2 7.7 3.3 0.9 3.9 5.4 5.1 2.9 1.3 5.9 0.5 0.8 0.9 1.5 2.5 1.2 1.3 : 0.8 : 3.2 3 : 1.6 4.5 : 0.7 0.9 1.2 2.7 1.4 1.7 3.9 : 1.0 : 8.7 8.1 : 0.8 8.0 : 1.0 1.0 1.9 2.3 1.0 0.8 27.3 26.7 28.8 29.5 26.4 20.1 29.7 14.1 25.2 21.0 27.4 28.7 22.7 25.2 32.3 26.8 46.4 43.8 38.1 42.2 49.4 46.3 44.1 25.4 63.4 40.0 42.4 48.3 45.6 35.8 39.1 47.7 0.917 0.253 0.632 0.931 0.929 0.436 4.8 6.5 6.8 4.7 5.3 5.9 : 4.6 0.920 0.365 4.4 3.8 0.254 7.2 0.742 3.0 3.3 3.1 26.8 23.9° 5t Nr. Key indicator Unit Year 0.681 1.000 1.641 5.4 5.8 2.7 4.1 3.2 1.507 0.089 3.4 5.7 26 28 26 24 23 25 28 33 23 26 21 25 27 27 30 33 18 4.5 16 4.5 9 : 16 4.7 22 4.2 19 5.1 18 5.5 17 6.6 20 5.0 12 0.9 12 1.1 13 2.4 20 1.2 8 : 10 : 21 3.9 23 73.0 23 68.2 38 80.2 32 72.6 9 28 70.8 70.9 10 70.3 13 76.4 11 68.5 17 74.8 35 28 82.8 76.7 20 76.9 37 70.9 44 73.0 18 78.3 54.9 50.3 72.0 58.8 40.9 41.9 56.1 55.0 41.1 50.9 65.2 60.1 61.1 65.4 70.4 65.1 84* 75.3 81.4 63 66 89 74.6 80.8 65 69 86 74.5 79.3 62 62 81 74.7 80.7 63 69 87 86* 75.5 75.5 80.6 82.7 67 65 70 68 88 75.2 82.7 60 63 78 74.2 79.2 64 67 91 76.3 82.4 67 70 82° 74.9 81.3 61 64 79 79 75.5 75.4 80.5 81.2 63 62 63 66 95 72.7 79.7 59 61 81 74.2 81.0 56 59 83 77.4 82.0 : : 78 75.4 80.2 61 62 99* 82~b 89 96 102 72 99 104 105 92 94* 89 111 111 98* 80~b 88 108 88 96 92 109 101 69 98 105 : 92 96* 89 113 109 99 99 76 113 111 88 104 100 : 93 93* 88 106 118 100 61 70 73 85 85 39 66 149* 115 100 79* 88 85 88 B DK D EL E F IRL I L NL A P FIN S UK 104* 101 79* EU-15 * = See comment in the corresponding portrait. The figure may be from another year (latest available) or may have some other limitation. (Reading notes are on the next page) 175 Annex I Key social indicators per Member State Reading note for each key indicators 3 4 EU-wide, the number of persons aged 65 and over corresponded to 24.3% of what is considered to be the working age population (15-64 years) in 2001. The net migration rate for the EU in 2001 was 3.1 per 1000 inhabitants. 5t In 2001, 19.4% of 18-24 year-olds in the EU had left the education system without completing a qualification beyond lower secondary schooling. 6t EU-wide, 8.4% of the population aged 25-64 had participated in education/training in the 4 weeks prior to the survey in 2001. 7 64.0% of the EU population aged 15-64 were in employment in 2001. 8at 38.6% of the EU population aged 55-64 were in employment in 2001. 8bt In 2001, the effective average exit age from the labour market was 59,9 years. 9t 7.4% of the EU labour force (those at work and those seeking work) were unemployed in 2001. 10 7.3% of the EU population aged 15-24 were unemployed in 2001. 11t 3.2% of the EU labour force (those at work and those seeking work) had been unemployed for at least one year in 2001. 12 In 2000, EU social protection expenditure represented 27.3% of Gross Domestic Product (GDP). 13 EU-wide, old-age and survivors benefits make up the largest item of social protection expenditure (46.4% of total benefits in 2000). 14 In 2000, EU public expenditure on active Labour Market Policy measures represented 0.681% of Gross Domestic Product (GDP). 15 As an average in EU Member States in 1999, the top (highest income) 20% of a Member State's population received 4.6 times as much of the Member State's total income as the bottom (poorest) 20% of the Member State's population. 16a EU-wide before social transfers, 24% of the population would have been living below the poverty line in 1999. 16b EU-wide after social transfers, 15% of the population were actually living below the poverty line in 1999. 17a EU-wide in 2002, 12.1% of population aged 0-65 years were living in households with no member in employment (excluding persons in households where all members are aged less than 18 years, or 18-24 years and in education, or 65 years and more and not working). 18 EU-wide, 23% of the seats in the national Parliaments (or Lower House) were occupied by women in 2001. 19 73.0% / 54.9 % of the EU male / female population aged 15-64 were in employment in 2001. 20 EU-wide, the average gross hourly earnings of women were 84% of the average gross hourly earnings of men in 1999. The population consists of all paid employees aged 16-64 that are 'at work 15+ hours per week'. 21a The average life expectancy at birth of a male / female citizen in the EU was 75.3 / 81.4 years in 2000. 21b On average, a male / female citizen in the EU should live to 63 / 66 without disability (1996 data). 22at 22b EU-wide there occurred 1 % less serious working accidents (resulting in more than three days' absence) per 100 000 persons in employment in 2000 than in 1998. EU-wide there occurred 21 % less fatal working accidents per 100 000 persons in employment in 2000 than in 1998. 176 Statistical portraits data - European Union Member States Annex II Annex II: Statistical data - European Union Member States 1 ECONOMY EU-15 Gross domestic product at current market prices 2001. Bn Euro 8 815 GDP growth rates, at constant prices (1995) Annual growth rate, 2000 Annual growth rate, 2001 Compared to the same quarter of the previous year, 2002Q1 Compared to the same quarter of the previous year, 2002Q2 EUR-12 B DK D EL E F IRL I L NL A P FIN S UK 6 811 257 180 2 063 130 650 1 464 115 1 217 21 425 211 123 136 234 1 589 3.5 1.5 3.5 1.4 4.0 1.0 3.0 1.0 3.0 0.6 4.1 4.1 4.1 2.8 3.8 1.8 11.5 5.9 2.9 1.8 7.5 3.5 3.5 1.1 3.0 1.0 3.5 1.7 6.1 0.7 3.6 1.2 3.1 1.9 0.4 0.3 -0.3 1.1 -0.2 4.3 2.0 0.4 2.9 0.0 : 0.4 -0.6 1.4 -1.9 1.0 1.1 0.7 0.6 0.3 1.9 0.1 : 2.0 1.0 : 0.2 : 0.1 : : : 1.6 1.2 104 100 94 119 104 105 172 191 110 112 111 112 70 74 97 103 103 100 97 100 25 900 17 100 24 000 23 200 23 200 Growth rates for 2002Q1 and 2002Q2 are calculated from seasonally adjusted data (except for Ireland). GDP per head (Index EU-15 = 100, in PPS) 1995 2001 100 100 101 100 113 106 118 119 110 104 66 67 78 83 GDP per head in PPS 2001 23 200 23 100 24 600 27 600 24 100 Net national income per head 2001, EU-15 = 100 100.0 95.3 109.4 136.3 106.0 55.8 69.3 104.2 113.4 91.3 172.4 113.0 110.0 51.8 109.0 109.6 119.4 Household consumption per head 2001, EU-15 = 100 100.0 94.1 60.7 69.7 93.0 144.1 96.6 109.6 54.6 96.2 96.4 129.3 99.8 116.3 110.1 15 500 19 200 23 300 27 700 24 400 44 300 26 000 97.3 105.0 Household consumption includes the consumption expenditure of non-profit institutions serving households. Net saving per head 2001, EU-15 = 100 100.0 105.7 171.4 162.4 76.9 60.0 91.9 113.6 253.3 98.1 : 196.1 118.1 20.5 190.4 97.9 56.9 Gross compensation per employee 2001, EU-15 = 100 100.0 93.2 109.9 151.3 114.5 32.6 67.9 106.9 : 72.2 211.6 115.8 114.4 : 106.6 131.8 125.6 Gross compensation per employee includes wages and salaries plus employers social contributions. Gross compensation of employees is measured according to the domestic concept, while the number of employees is taken from the national concept. This has a significant effect on the ratio for countries such as Luxembourg with a relatively high proportion of workers living in neighbouring countries. Source: Eurostat - National Accounts. General government debt (% of GDP) 1999 2000 2001 67.8 63.9 63.0 72.5 115.0 70.1 109.3 69.1 107.5 General government deficit (-) (% of GDP) 1999 2000 2001 -0.7 1.1 -0.6 -1.3 0.2 -1.3 -0.6 0.1 0.2 52.7 46.8 44.5 61.3 60.3 59.8 103.8 102.8 99.7 63.1 60.4 57.2 58.5 57.4 57.2 49.6 114.5 39.0 110.6 36.6 109.4 6.0 5.6 5.5 63.1 56.0 53.2 64.9 63.6 61.7 54.2 53.4 55.6 46.8 44.0 43.6 65.0 55.3 56.0 45.2 42.4 39.0 3.1 2.5 2.5 -1.6 1.3 -2.7 -1.7 -0.8 0.1 -1.1 -0.3 0.0 -1.6 -1.3 -1.4 2.3 4.5 1.7 -1.8 -0.5 -1.4 3.8 5.8 5.0 0.4 2.2 0.2 -2.2 -1.5 0.1 -2.2 -1.5 -2.2 1.9 7.0 4.9 1.6 3.7 4.7 1.1 4.1 0.9 2.3 1.9 2.2 2.2 2.6 1.0 0.7 1.0 4.2 3.8 3.6 3.6 2.4 3.7 3.4 3.5 2.2 1.5 1.5 1.5 4.0 5.0 4.5 4.2 2.4 2.4 2.2 2.4 2.4 1.3 1.3 1.9 5.3 3.8 3.9 3.8 2.8 1.7 1.5 1.5 4.3 3.4 3.5 3.6 2.6 1.8 1.5 2.0 2.9 1.7 1.7 1.8 1.4 0.8 0.6 1.1 2.2 1.7 3.8 3.0 1.8 4.4 2.3 1.7 4.6 1.9 3.7 2.3 2.6 1.2 Source: Eurostat - National and Financial Accounts. Annual inflation rate compared to the same month of the previous year July 2001 May 2002 June 2002 July 2002 2.5 1.8 1.6 1.8 2.6 2.0 1.8 2.0 2.7 1.4 0.8 1.1 12-month average annual inflation rate, 12-month average rate July 2002 2.1 2.3 1.9 "The annual inflation rate measures the price change between the current month and the same month the previous year. This measure is responsive to recent changes in price levels but can be influenced by one-off effects in either month. The 12-month average rate overcomes this volatility by comparing average Harmonized Indices of Consumer Prices (HICPs) in the latest 12 months to the average of the previous 12 months. This measure is less sensitive to transient changes in prices. Source: Eurostat - Price statistics." Interest rates: 10-year government bond yields (EMU convergence criterion series), monthly average August 2001 June 2002 July 2002 August 2002 5.03 5.17 5.02 4.73 5.07 5.16 5.03 4.73 5.15 5.24 5.09 4.80 5.12 5.27 5.13 4.87 4.82 5.02 4.87 4.59 5;33 5.37 5.21 5.21 5.16 5.23 5.07 4.78 4.95 5.11 4.96 4.67 5.01 5.25 5.11 4.84 5.22 5.26 5.11 4.83 4.81 5.09 4.87 4.70 4.98 5.16 4.99 4.71 5.09 5.19 5.08 4.78 5.23 5.28 5.18 4.93 5.06 5.26 5.10 4.81 5.16 5.52 5.37 5.13 5.07 5.19 5.02 4.67 9.40 4.73 5.58 5.19 6.32 4.67 5.52 4.86 6.15 4.63 5.40 4.96 6.32 4.68 5.56 5.07 8.56 4.79 5.60 5.16 7.07 4,73 5.48 5.04 8.02 4.99 5.37 5.11 7.94 5.02 5.33 5.01 Interest rates: 10-year government bond yields (EMU convergence criterion series), annual average 1996 1999 2000 2001 7.47 4.73 5.42 5.00 7.23 4.66 5.44 5.03 6.49 4.75 5.59 5;13 7.19 4.91 5.64 5.08 6.22 4.50 5.26 4.80 14.36 6.30 6.10 5.30 8.73 4.73 5.53 5.12 6;31 4.61 5.39 4.94 7.29 4.72 5.51 5.01 The interest rate figures given for the euro-zone refer to EUR-11 (I.e. excluding Greece) for years before 2001. Source: Eurostat - Financial indicators. 177 Annex II Statistical portraits data - European Union Member States 2 POPULATION EU-15 Total population (1000) 1.1.1960 1.1.1980 1.1.2000 1.1.2001, revised estimate 1.1.2002, first esimate 2010, baseline scenario, revision 1999 2015, baseline scenario, revision 1999 2020, baseline scenario, revision 1999 2050, baseline scenario, revision 1999 314 354 375 377 379 826 572 974 988 449 B 9 9 10 10 10 129 855 239 263 292 DK 4 5 5 5 5 565 122 330 349 367 D 72 78 82 82 82 543 180 163 260 360 EL 8 9 10 10 10 300 588 543 565 596 E 30 37 39 40 40 327 242 442 122 428 F 45 53 58 59 59 465 731 744 040 344 IRL 2 3 3 3 3 836 393 777 826 874 50 56 57 57 58 I L NL 026 388 680 844 018 313 363 436 441 447 11 14 15 15 16 417 091 864 987 101 A 7 7 8 8 8 030 546 103 121 140 P 8 9 9 10 10 826 714 998 243 303 FIN 4 4 5 5 5 413 771 171 181 195 S 7 8 8 8 8 471 303 861 883 910 UK 52 56 59 59 60 164 285 623 863 075 383 397 10 352 5 476 83 435 10 768 39 857 61 369 4 141 57 277 471 16 690 8 149 10 309 5 267 8 951 60 885 385 186 10 419 5 514 83 477 10 817 39 824 62 192 4 295 56 761 485 16 993 8 163 10 437 5 295 9 017 61 495 385 984 10 483 5 554 83 295 10 806 39 528 62 840 4 427 55 985 500 17 270 8 170 10 526 5 314 9 115 62 173 364 485 10 104 5 555 76 006 10 231 35 145 62 153 4 757 48 072 559 17 679 7 612 10 669 4 951 9 197 61 793 1.9 1.4 0.5 2.4 -0.3 2.7 3.5 1.2 2.3 The new estimates for 1.1.2001 and 1.1.2002 could not be incorporated into the portrait "2. Demography, households and families" in Section 3. Population growth rates (per 1000 population), 2000 Total increase Natural increase Net migration 2.8 1.0 1.8 2.3 1.1 1.2 3.6 1.7 1.9 0.4 -0.9 1.3 2.1 -0.2 2.3 1.2 0.7 0.5 5.0 4.1 0.9 11.4 6.1 5.3 2.8 -0.3 3.1 12.8 4.5 8.3 7.5 4.1 3.3 2.3 0.2 2.1 2.5 1.4 1.1 The increase in total population is made up of the natural increase (live births less deaths) and net migration. Net migration is estimated on the basis of the difference between population change and natural increase (corrected net migration). Population structure (percentage of total), 2000 Total 0-19 20-59 60-79 80 and over 100 23.0 55.4 18.0 3.7 100 23.6 54.5 18.4 3.5 100 23.7 56.6 15.8 3.9 100 21.3 55.7 19.4 3.6 100 21.8 55.1 19.6 3.5 100 21.7 56.7 17.9 3.7 100 25.6 53.9 16.9 3.6 100 30.8 54.1 12.6 2.5 100 19.8 56.3 20.0 3.9 100 24.4 56.5 16.0 3.1 100 24.4 57.5 15.0 3.2 100 22.8 56.8 16.9 3.5 100 23.5 55.9 17.8 2.8 100 24.7 55.5 16.5 3.3 100 24.2 53.6 17.2 4.9 100 25.3 54.3 16.5 4.0 1 795 983 12 915 1 603 5940 11 145 826 8 290 82 2 946 1 360 1 677 943 1 638 1 1390 -11 -6 -11 -1 -4 -4 6 -10 -3 -2 -18 7 -12 -18 -11 1 240 620 9123 1476 5778 7722 658 6823 49 1877 954 1484 662 1025 7244 -1 15 -2 -26 -31 -4 -17 -17 30 11 -1 -21 -3 10 7 4 434 2 344 35 831 4 446 17 158 25 441 1 549 25 324 197 7 299 3 611 4 245 2 258 3 678 25 549 -6 -7 -3 3 2 -3 19 -6 0 -6 -3 4 -10 -3 -1 1042 595 10 955 1 199 3 960 5 473 319 6 808 44 1 583 912 1 060 543 987 6 070 Source: Eurostat - Demographic statistics. Population aged 0-14 2000 (1000s) 63 533 percentage change. 2000/2015 -8 Population aged 15-24 2000 (1000s) 46 736 percentage change. 2000/2015 -7 Population aged 25-54 2000 (1000s) 163 365 percentage change, 2000/2015 -3 Population aged 55-64 2000 (1000s) 41 549 percentage change, 2000/2015 19 Population aged 65 and over 2000 (1000s) 60 988 percentage change, 2000/2015 22 Population aged 80 and over 2000 (1000s) 13 752 percentage change, 2000/2015 48 36 16 3 13 25 46 49 9 41 41 16 18 37 14 23 1 712 790 13 313 1 819 6 596 9 419 424 1 0343 62 2 154 1 253 1 535 766 1 533 9 268 17 28 28 20 15 23 32 22 32 36 23 16 36 21 18 353 208 2897 373 1 453 2 117 95 2 240 13 501 278 285 171 436 2 332 61 7 49 71 59 66 26 63 67 36 38 51 44 6 18 119 151 40 786 86 710 14 331 14 476 : 14 744 6 807 49 839 15 266 354 077 115 574 Source: Eurostat - Demographic Statistics; baseline demographic scenario, projection 1995, revision 1999. Immigration by main group of citizenship, 1999 Total Nationals Nationals of other EU Member State Non EU nationals 2 062 982 510 137 68 466 10 682 51 372 22 542 874 023 200 150 12 630 : 127 365 28 243 57 846 : 47 522 25 922 171 967 12 794 28 816 1 018 354 588 1 198 257 28 022 29 762 7 983 20 847 135 268 538 605 2 888 9 742 32 104 67 018 5 551 52 295 14 695 6 905 9 240 133 911 8 204 3 572 20 439 57 926 13 326 59 053 4 568 9 908 1 521 6 416 8 836 25 737 61 943 176 560 672 048 116 410 : : : : : : 29 000 : 46 273 38 984 8 075 1 172 59 023 38 358 66 923 19 644 : : 11 966 9 966 35 705 22 123 245 340 114 862 141 205 414 433 : : : : : : : : 2 173 5 116 5 560 1 343 10 127 10 538 7 653 39 626 : : 947 1 053 6 365 7 217 48 693 81 785 DK and EL: 1998. I: 1996. Emigration by main group of citizenship, 1999 Total 1 256 000 41 307 40 340 Nationals 403 139 16 927 24 693 Nationals of other EU Member State 244 527 15 997 5 807 Non EU nationals 579 334 8 383 9 840 DK: 1998. IRL and I: 1997. Net migration by main group of citizenship, 1999 Total Nationals Nationals of other EU Member State Non EU nationals : : 27 159 - 6 245 11 032 - 2 151 201 975 83 740 : : : : : : : : : : 4 719 - 154 60 128 2 428 19 787 - 5 313 : : 2 778 - 3 159 14 134 - 6 857 108 737 712 : : 12 025 21 379 2 176 11 007 - 5 937 124 172 : : : : : : : : : : 2 644 2 229 10 312 47 388 5 673 19 427 : : 574 5 363 2 471 18 520 13 250 94 775 DK: 1998. 178 Statistical portraits data - European Union Member States Annex II 2 POPULATION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK Population by main group of citizenship, in thousands, 2000 (or latest data) Total Nationals Foreigners Nationals of other EU Member State Non EU nationals 374 667 355 974 18 692 10 239 9 386 853 5 314 5 057 256 82 163 74 820 7 344 10 487 10 325 161 39 442 38 640 801 58 521 55 258 3 263 3 787 3 660 127 57 680 56 409 1 271 424 276 148 15 864 15 212 652 8 103 7 349 754 9 998 9 807 191 5 171 5 084 88 8 861 8 374 487 58 614 56 317 2 298 5 801 12 892 564 290 53 203 1 859 5 485 45 116 312 489 1 195 2 068 92 34 149 1 122 131 16 196 456 99 654 52 138 16 71 177 310 859 1 439 DK: 1999. EL: 1997. F: 1999. L: 1998. UK: 1999. A: The breakdown of foreigners calculated using the 1998 ratio of Nationals of other EU Member States to Non EU nationals. The EU-15 figures here are just the sums of the other figures in the row. Since five countries' data is earlier than 2000 data. the EU-15 total population figure given in the table is too little. The current estimate is 375 974 000. It will be revised in spring 2002 based on revision of at least French and Spanish data. Population by main group of citizenship, in %, 2000 (or latest data) Total Nationals Foreigners Nationals of other EU Member State Non EU nationals 95.0 5.0 91.7 8.3 95.2 4.8 91.1 8.9 98.5 1.5 98.0 2.0 94.4 5.6 96.7 3.3 97.8 2.2 65.1 34.9 95.9 4.1 90.7 9.3 98.1 1.9 98.3 1.7 94.5 5.5 96.1 3.9 1.5 3.4 5.5 2.8 1.0 3.8 2.3 6.7 0.4 1.1 0.8 1.2 2.0 3.5 2.4 0.9 0.3 1.9 31.0 3.8 1.2 2.9 1.2 7.9 0.5 1.4 0.3 1.4 2.0 3.5 1.5 2.5 DK: 1999. EL: 1997. F: 1999. L: 1998. UK: 1999. A: breakdown for foreigners: 1998. Asylum applications, 1 000s 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 397.0 511.2 672.4 516.7 300.3 263.7 227.8 242.8 295.5 352.5 12.9 15.4 17.7 26.7 14.3 11.4 12.4 11.8 22.0 35.7 5.3 4.6 13.9 14.3 6.7 5.1 5.9 5.1 5.7 6.5 193.1 256.1 438.2 322.6 127.2 127.9 117.3 104.4 98.6 95.1 4.1 2.7 2.1 0.9 1.1 1.3 1.6 4.4 3.0 1.5 8.6 8.1 11.7 12.6 12.0 5.7 4.7 5.0 4.9 8.4 54.8 47.4 28.9 27.6 26.0 20.4 17.4 21.4 22.4 30.9 0.1 0.0 0.0 0.1 0.4 0.4 1.2 3.9 4.6 7.7 3.6 24.5 2.6 1.3 1.8 1.8 0.7 1.9 13.1 18.5 0.1 0.2 0.1 0.2 0.3 0.3 0.3 0.4 1.7 2.9 21.2 21.6 20.3 35.4 52.6 29.3 22.9 34.4 45.2 39.3 22.8 27.3 16.2 4.7 5.1 5.9 7.0 6.7 13.8 20.1 0.1 0.2 0.7 2.1 0.6 0.3 0.3 0.3 0.4 0.3 2.7 2.1 3.6 2.0 0.8 0.8 0.7 1.0 1.3 3.1 29.4 27.4 84.0 37.6 18.6 9.0 5.8 9.7 12.8 11.2 38.2 73.4 32.3 28.5 32.8 44.0 29.6 32.5 46.0 71.2 Rate per 1 000 inhabitants. 1999 0.9 3.5 1.2 1.2 0.1 0.2 0.5 2.1 0.3 6.8 2.5 2.5 0.0 0.6 1.3 1.2 B: excluding dependent children. Figure for 1999 is calculated as the sum of monthly data supplied to Eurostat. I: excluding dependent children. DK: excluding applications made outside Denmank and rejected applications at the border. D: excluding repeat applications. Includes dependent children if the parents requested asylum for them. EL: figures for 1989-92 are the sum of the applications registered with the Greek authorities and those registered with UNHCR (United Nations High Commission for Refugees). E: up to 1998 - excluding dependants; 1999 - including dependants. F: excluding children and some accompanying adults. NL, A: excluding displaced persons from the former Yugoslavia granted exceptional leave to remain. S: excluding repeat applications. UK: excluding dependents. Source: Eurostat - Migration Statistics. Number of households (thousands), 2001 155 842 4 294 2 457 37 853 3 993 13 184 24 477 1 291 21 968 172 6 850 3 298 3 410 2 382 4 394 25 820 Average number of persons per household 1981/82 2.8 2.7 1991 2.6 2.6 2001 2.4 2.4 2.4 2.2 2.2 2.5 2.3 2.1 3.1 2.8 2.6 3.6 3.3 3.0 2.7 2.5 2.4 3.6 3.3 3.0 3.0 2.8 2.6 2.8 2.7 2.5 2.8 2.4 2.3 2.7 2.6 2.4 3.3 3.1 2.9 2.6 2.3 2.1 2.3 2.1 2.0 2.7 2.5 2.3 DK: 2000. S: 1990 and 2000. DK, IRL (2001). FIN, S: data from national sources. Source: Eurostat - Censuses of Population (1981/82). European Union Labour Force Survey (1991 and 2001). Population living in private households by household type, 2000 Total population 1 adult without dependent children ... aged under 30 ... aged 30-64 ... aged 65 or more ... Male ... ... aged under 30 ... ... aged 30-64 ... ... aged 65 or more ... Female ... ... aged under 30 ... ... aged 30-64 ... ... aged 65 or more 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 12 2 5 5 5 1 3 1 7 1 2 4 12 1 5 6 5 1 3 1 8 1 2 5 17 4 7 6 8 2 4 1 9 1 2 5 16 3 7 6 7 1 4 1 9 1 3 5 8 1 3 4 3 1 1 1 5 1 1 3 5 0 2 3 2 0 1 1 3 0 1 2 13 2 5 5 5 1 3 1 8 1 3 4 7 1 3 3 4 0 2 1 4 0 1 2 9 0 3 5 3 0 2 1 6 0 2 4 10 2 5 4 4 1 3 1 5 1 2 3 14 3 6 5 6 2 4 1 8 1 3 4 12 2 6 5 5 1 3 1 8 1 3 4 5 0 1 3 1 0 1 1 3 0 1 2 17 4 8 6 7 2 4 1 10 2 4 4 20 5 9 6 10 3 5 2 10 2 3 5 13 2 6 6 6 1 3 2 7 1 3 4 179 Annex II Statistical portraits data - European Union Member States 2 POPULATION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK 2 adults without dependent children ... both younger 65 ... at least one aged 65 or more 24 14 25 14 28 19 29 18 22 9 17 7 25 15 14 8 18 8 19 12 29 20 23 14 16 8 26 16 25 15 27 17 10 11 9 11 13 10 10 6 10 7 9 9 9 9 10 10 3 or more adults without dependent children 14 11 8 10 21 23 8 13 21 12 10 15 18 5 1 11 4 5 3 4 2 2 5 3 2 3 3 3 3 5 7 8 2 adults with dependent children … 1 child … 2 children … 3 or more children 35 11 17 8 40 12 17 11 35 11 15 9 33 12 15 6 34 10 18 5 34 11 18 5 42 12 18 12 39 8 15 17 36 13 18 5 44 14 19 11 35 9 17 8 33 11 16 6 38 16 17 5 41 13 17 11 45 12 20 13 32 9 15 9 3 or more adults with dependent children 11 7 10 7 13 20 8 24 13 12 9 14 20 6 1 8 1 adult with dependent children Note: Dependent children include all children younger than 15 years plus all those persons aged 15-24 who are economically inactive (mainly in education) and who are living with at least one of their parents. Source: Eurostat - European Labour Force Survey 2000. DK, IRL, FIN, S: 1997. European Community Household Panel. UDB September 2001. Population living in private households by household type, 1988 Total population 1 adult without dependent children 2 adults without dependent children 3 or more adults without dependent children 1 adult with dependent children 2 adults with dependent children 3 or more adults with dependent children 100 100 : 100 100 100 100 100 100 100 100 : 100 : : 100 10 11 : 15 6 3 11 6 8 9 11 : 4 : : 10 21 21 : 25 18 13 22 13 18 21 23 : 15 : : 25 14 10 : 14 15 17 9 12 18 16 11 : 15 : : 16 3 3 : 3 2 1 3 3 2 2 3 : 2 : : 4 38 46 : 33 42 37 46 46 40 38 41 : 34 : : 35 14 8 : 10 18 29 9 21 14 15 10 : 29 : : 11 Source: Eurostat - European Labour Force Survey 1988. Elderly population by household situation and age-group, 2010 Population aged 65 and over Persons living alone Persons living with a partner Other household situations Institutional households 32 54 9 4 35 48 13 4 42 52 2 5 35 56 5 3 27 57 10 6 22 58 18 2 34 54 6 5 32 42 17 9 27 52 14 7 28 52 16 4 33 55 3 9 31 52 13 4 23 57 18 2 38 48 9 5 42 54 2 2 35 52 8 4 27 63 8 2 29 56 13 2 36 60 2 3 30 64 4 1 23 65 8 4 18 67 13 1 29 64 5 2 30 49 15 6 23 61 12 4 24 61 12 3 30 65 2 3 26 60 12 2 20 64 15 1 34 56 8 2 33 64 2 1 30 61 7 2 45 31 14 10 51 28 14 8 62 26 2 10 52 29 9 10 36 35 16 12 30 34 32 4 46 34 10 10 39 19 23 19 39 30 17 13 38 28 25 9 44 27 5 24 43 29 17 11 32 35 30 4 49 23 14 14 62 30 3 4 50 31 11 8 Population aged 65-79 years Persons living alone Persons living with a partner Other household situations Institutional households Population aged 80+ Persons living alone Persons living with a partner Other household situations Institutional households The category 'Persons living with a partner' includes elderly persons who live with their partner and other adults or children. Source: Eurostat - 1995-based (baseline) household scenarios. Crude marriage rate (per 1 000 population) 1960 1970 1980 1990 1999 2000 8.0 7.7 6.3 6.0 5.1 : 7.2 7.6 6.7 6.5 4.3 4.4 7.8 7.4 5.2 6.1 6.7 : 9.5 7.4 6.3 6.5 5.2 5.1 7.0 7.7 6.5 5.8 5.9 5.9 7.7 7.3 5.9 5.7 5.2 : 7.0 7.8 6.2 5.1 4.8 5.1 5.5 7.0 6.4 5.1 4.9 5.0 7.7 7.3 5.7 5.6 4.8 : 7.1 6.4 5.9 6.1 4.8 4.9 7.8 9.5 6.4 6.4 5.7 5.5 8.3 7.1 6.2 5.8 4.9 4.8 7.8 9.4 7.4 7.2 6.9 6.4 7.4 8.8 6.1 5.0 4.7 5.1 6.7 5.4 4.5 4.7 4.0 4.5 7.5 8.5 7.4 6.5 5.1 : 2.41 2.42 1.64 1.33 1.25 2.28 1.98 1.49 1.61 1.78 3.12 2.57 1.60 1.62 1.72 2.69 2.29 1.65 1.45 1.32 3.1 2.83 2.18 1.57 1.54 2.72 1.82 1.63 1.78 1.73 2.2 1.92 1.68 2.13 1.54 2.72 2.43 1.90 1.83 1.64 The crude marriage rate is the ratio of the number of marriages to the mean population in a given year. Total fertility rate 1960 1970 1980 1990 2000 2.59 2.38 1.82 1.57 1.53 2.56 2.25 1.68 1.62 1.65 2.57 1.95 1.55 1.67 1.76 2.37 2.03 1.56 1.45 1.34 2.28 2.39 2.21 1.39 1.30 2.86 2.90 2.20 1.36 1.22 2.73 2.47 1.95 1.78 1.89 3.76 3.93 3.23 2.11 1.89 The total fertility rate is the average number of children that would be born alive to a woman during her lifetime if current fertility rates were to continue. 180 Statistical portraits data - European Union Member States Annex II 2 POPULATION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK Percentage of live births outside marriage 1960 5.1 2.1 1970 5.6 2.8 1980 9.6 4.1 1990 19.6 11.6 1999 27.2 20.1 2000 : : 7.8 11.0 33.2 46.4 44.9 : 7.6 7.2 11.9 15.3 21.6 23.0 1.2 1.1 1.5 2.2 4.0 4.0 2.3 1.4 3.9 9.6 14.1 : 6.1 6.9 11.4 30.1 40.7 : 1.6 2.7 5.0 14.6 30.9 31.8 2.4 2.2 4.3 6.5 9.2 : 3.2 4.0 6.0 12.8 18.6 21.9 1.4 2.1 4.1 11.4 22.8 25.1 13.0 12.8 17.8 23.6 30.5 31.3 9.5 7.3 9.2 14.7 20.8 22.2 4.0 5.8 13.1 25.2 38.7 39.2 11.3 18.6 39.7 47.0 55.3 55.3 5.2 8.0 11.5 27.9 38.8 39.5 Crude divorce rate (per 1 000 population) 1960 0.5 0.5 1970 0.8 0.7 1980 1.4 1.5 1990 1.7 2.0 1999 1.8 2.6 2000 : 2.6 1.5 1.9 2.7 2.7 2.5 : 1.0 1.3 1.8 2.0 2.3 : 0.3 0.4 0.7 0.6 0.9 0.9 0.6 0.9 : 0.7 0.8 1.5 1.9 2.0 : : : 0.2 0.5 0.6 0.6 0.5 0.6 1.6 2.0 2.4 2.3 0.5 0.8 1.8 1.9 2.1 2.1 1.1 1.4 1.8 2.1 2.3 2.4 0.1 0.1 0.6 0.9 1.8 1.9 0.8 1.3 2.0 2.6 2.7 2.7 1.2 1.6 2.4 2.3 2.4 2.4 0.5 1.1 2.8 2.9 2.7 : 2 3 5 8 9 : 14 26 40 40 10 17 25 33 33 : 18 27 34 36 : 4 9 16 17 : 22 33 41 45 : 32 38 46 47 : 23 34 42 43 The crude divorce rate is the ratio of the number of divorces to the mean population in a given year. Proportion of marriages dissolved by divorce, by marriage cohort (%) 1950 1960 1970 1980 1983 : 15 22 28 29 : 15 26 35 37 : 29 40 44 43 : 18 28 36 36 : 6 8 12 13 : 5 8 12 14 : 17 28 35 35 : : : The sum of the divorce rates by duration of marriage calculated for n calendar years for a marriage cohort gives the proportion of marriages dissolved by divorce for this generation after n years. In practice, the divorce rates for advanced durations of marriage can be estimated using the rates for previous generations, without waiting for the married life of the cohort to be completely over. This produces an estimate of the definitive proportion of marriages, which will end in divorce for this generation. EU-15, UK: Scotland and Northern Ireland not included. Mean marriage duration at divorce by marriage cohort, years 1950 1960 1970 1980 1983 : 14.4 14.0 12.7 12.5 : 17.5 16.6 15.0 14.9 : 14.4 11.9 10.7 10.8 : 12.5 12.0 11.5 11.8 : 14.6 14.3 12.3 12.1 : 19.0 19.8 16.6 15.6 : 15.5 15.5 14.2 14.0 : : : 21.4 21.0 20.5 17.4 17.1 : 17.5 15.6 13.6 13.2 16.9 17.2 14.8 12.7 12.7 : 11.2 11.9 11.4 11.3 : 22.7 19.0 16.1 15.7 : 15.5 14.6 14.2 13.7 : 14.9 13.3 12.1 12.1 : 16.3 13.3 12.0 11.6 8 1 12 3 41 10 29 4 11 2 27 7 56 15 30 9 15 5 61 21 70 23 53 13 EU-15, UK: Scotland and Northern Ireland not included. Source: Eurostat - Demographic Statistics. Percentage of couples living in a consensual union, 1998 Age group 16-29 years Total population 33 9 35 9 57 17 35 9 L: 1996. FIN: 1997. S: 1997 data from national Income distribution survey. Source: ECHP users' database. version December 2001. Percentage of the population aged at least 16 years whose daily activities include looking after children or other persons (1) without pay, by sex, 1998 Males Females 18 33 23 41 26 34 19 28 11 35 12 32 13 24 16 40 20 43 21 36 32 43 14 36 7 31 22 31 : : 20 31 18 26 : : 8 18 Percentage of the population aged at least 16 years whose daily activities include looking after children without pay, by sex, 1998 Males Females 14 27 19 36 23 28 17 26 10 32 10 26 11 21 14 36 18 39 19 32 28 39 12 32 6 26 Percentage of the population aged at least 16 years whose daily activities include looking after persons other than children (1) without pay, by sex, 1998 Males Females 5 8 5 8 3 2 2 6 3 7 3 5 3 6 4 8 (1) Providing care to sick. disabled or frail adults. Source: Eurostat - European Community Household Panel (ECHP). UDB December 2001 version. L: 1996. FIN: 1997. 181 4 7 5 9 2 7 1 8 4 6 : : 13 16 Annex II Statistical portraits data - European Union Member States 3 EDUCATION AND TRAINING EU-15 B DK D EL E F IRL I L NL A P FIN S UK Population aged 25-64 by age group. sex and educational attainment level (%), 2000 25-64 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 25-29 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 30-49 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 50-64 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 36.4 42.4 21.2 41.7 31.2 27.1 20.2 54.0 25.8 18.7 57.4 23.8 48.8 34.3 16.9 62.9 15.3 21.8 37.7 40.7 21.6 50.7 27.1 22.2 54.8 35.6 9.6 39.1 42.6 18.3 33.9 42.0 24.1 23.8 61.9 14.2 78.4 11.7 9.8 26.8 40.5 32.6 22.8 47.5 29.7 19.3 52.5 28.1 33.7 43.5 22.8 42.3 31.1 26.6 18.5 57.1 24.4 14.2 56.8 28.9 46.7 34.4 18.8 61.4 15.8 22.8 34.8 44.0 21.1 54.3 23.2 22.5 54.1 36.0 9.9 34.8 44.4 20.8 30.2 43.1 26.7 17.0 65.9 17.1 80.1 11.7 8.2 28.4 42.2 29.4 24.3 48.3 27.4 16.3 54.0 29.6 39.1 41.3 19.6 41.1 31.2 27.7 22.0 50.8 27.2 23.3 58.0 18.6 50.8 34.1 15.1 64.2 14.9 20.9 40.6 37.4 22.0 47.1 30.9 22.0 55.5 35.1 9.4 43.5 40.8 15.7 37.8 40.8 21.4 30.6 58.0 11.4 76.7 11.8 11.5 25.3 38.8 35.9 21.2 46.7 32.1 22.6 50.9 26.5 24.3 50.0 25.7 19.8 42.5 37.7 13.5 61.2 25.3 16.3 65.7 18.0 25.3 53.8 20.9 38.6 22.0 39.5 21.1 43.4 35.5 : : : 36.7 54.0 9.2 29.9 45.3 24.8 24.2 48.0 27.8 16.1 70.7 13.3 62.4 23.3 14.3 13.2 50.5 36.3 13.2 52.3 34.5 9.9 57.5 32.6 25.4 50.8 23.8 22.4 43.6 34.1 15.6 63.4 21.0 14.7 67.8 17.5 29.4 52.6 18.0 43.1 23.0 33.9 21.3 46.5 32.2 : : : 39.8 52.4 7.8 32.4 45.1 22.6 26.1 48.0 25.9 12.0 73.7 14.3 65.7 22.8 11.6 15.7 55.8 28.5 12.8 56.7 30.5 9.6 56.2 34.2 23.3 49.2 27.6 17.2 41.3 41.5 11.5 59.0 29.5 17.9 63.6 18.5 21.1 55.0 23.9 34.0 20.9 45.0 20.8 40.4 38.8 : : : 33.7 55.6 10.7 27.3 45.5 27.2 22.3 47.9 29.8 20.0 67.8 12.3 59.2 23.8 16.9 10.5 44.9 44.7 13.6 47.7 38.7 10.3 58.9 30.8 31.9 45.1 22.9 37.2 33.2 29.6 17.3 53.4 29.3 15.7 58.0 26.3 40.7 38.7 20.7 57.7 18.7 23.6 33.9 44.0 22.1 : : : 49.1 39.7 11.2 36.3 45.3 18.4 30.7 44.0 25.3 19.8 64.4 15.9 78.9 11.2 9.9 18.6 45.0 36.3 18.0 50.2 31.8 15.4 55.3 29.2 30.4 45.5 24.1 39.7 31.9 28.4 16.6 57.1 26.4 13.1 56.3 30.6 39.4 38.1 22.5 56.9 18.6 24.5 31.9 46.8 21.3 : : : 49.4 39.3 11.3 32.3 46.6 21.0 28.9 43.5 27.7 14.5 67.8 17.7 80.6 11.1 8.3 21.2 47.7 31.2 19.8 51.0 29.3 12.9 56.4 30.8 33.5 44.7 21.8 34.7 34.5 30.8 18.2 49.4 32.4 18.5 59.7 21.8 41.8 39.2 18.9 58.4 18.8 22.8 35.9 41.3 22.8 : : : 48.8 40.1 11.1 40.4 43.8 15.7 32.6 44.5 22.9 25.1 60.8 14.0 77.2 11.3 11.5 16.0 42.3 41.7 16.1 49.5 34.4 18.0 54.3 27.7 48.9 34.6 16.4 58.6 23.0 18.4 27.2 52.3 20.5 24.3 54.0 21.7 69.2 20.8 10.0 82.0 6.9 11.1 51.9 33.5 14.7 : : : 72.4 20.4 7.2 48.6 36.3 15.1 43.8 35.9 20.3 34.4 53.9 11.7 87.5 5.6 6.9 44.0 30.4 25.6 33.3 41.8 24.9 31.8 44.4 23.7 42.8 37.2 20.1 55.3 24.5 20.2 22.5 54.9 22.6 15.9 54.3 29.8 63.9 22.2 13.8 77.3 7.9 14.9 46.1 37.9 16.0 : : : 68.4 23.2 8.4 40.6 39.8 19.6 34.2 40.4 25.4 23.8 59.1 17.1 87.6 6.3 6.1 44.2 29.0 26.8 35.3 41.3 23.4 25.6 48.8 25.6 55.2 32.0 12.7 61.8 21.5 16.7 32.2 49.6 18.2 32.8 53.7 13.5 74.0 19.5 6.4 86.4 6.0 7.5 57.4 29.2 13.4 : : : 76.3 17.7 6.0 56.7 32.7 10.6 53.6 31.3 15.1 44.6 48.9 6.5 87.4 4.7 7.9 43.8 31.8 24.5 31.3 42.3 26.4 39.6 39.0 21.4 The levels of education are defined according to ISCED (International Standard Classification of Education). Less than upper secondary corresponds to ISCED 0-2. upper secondary level to ISCED 3-4 (including thus post-secondary non-tertiary education) and tertiary education to ISCED 5-6. IRL 1997 data. UK - GCSE 'O' levels are included under ISCED 3. Unemployment rates of the population aged 25-59 by sex and level of education, 2000 Males and Females ..Less than upper secondary ..Upper secondary ..Tertiary education Males ..Less than upper secondary ..Upper secondary ..Tertiary education Females ..Less than upper secondary ..Upper secondary ..Tertiary education 11 7 4 9 5 2 7 4 3 14 8 4 9 11 7 14 11 9 14 8 5 : : : 10 7 6 3 2 1 3 2 2 8 2 2 4 4 2 12 9 5 8 5 3 9 4 2 9 6 4 7 4 2 5 3 3 15 8 4 6 7 5 10 7 6 12 6 5 : : : 8 5 4 3 1 1 3 1 1 10 2 2 3 2 2 11 8 4 8 5 4 12 5 2 14 8 5 13 7 3 8 5 3 13 9 5 14 17 10 22 18 13 16 11 6 : : : 15 11 8 4 3 1 4 2 2 7 2 2 4 5 3 13 10 6 8 5 2 6 4 2 20 9 19 30 18 8 17 28 22 9 21 32 22 14 19 31 19 12 17 28 24 17 20 34 21 7 20 35 18 6 16 29 24 8 24 41 Participation (%) in education and training in the last four weeks of those aged 25-64 by sex and educational attainment level, 2000 ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 8 2 10 16 8 2 9 14 9 3 10 18 7 2 7 14 8 3 8 15 6 2 6 12 21 11 20 31 18 9 16 29 24 13 24 33 5 2 6 7 6 2 6 6 5 1 5 9 1 0 2 2 1 0 2 2 1 0 2 2 5 1 9 13 4 1 9 11 5 1 9 15 3 1 2 7 3 1 2 7 3 1 3 7 5 2 5 12 5 : : : 5 : : : 5 2 10 10 5 2 10 9 5 2 10 11 5 1 6 11 6 1 7 12 4 1 4 11 16 9 18 21 16 11 19 19 15 8 16 23 8 4 9 15 9 : : : 7 : : : 3 1 14 11 3 1 16 11 3 1 13 10 F. NL. P - Information on training is collected only if it is under way on the date of the survey. Consequently, the extent of training may be underestimated. IRL, A - 1997 data. UK - GCSE 'O' levels are included under ISCED 3. Source: Eurostat - European Union Labour Force Survey. 182 Statistical portraits data - European Union Member States Annex II 3 EDUCATION AND TRAINING (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK 92 91 80 70 75 80 89 90 76 90 71 77 75 81 94 94 84 80 72 85 91 93 93 100 68 73 105 122 119 67 107 115 77 117 123 : : 107 70 93 97 76 95 100 102 134 127 89 112 117 108 126 136 59 107 114 22 22 22 21 21 21 23 24 23 23 : : 23 23 22 25 26 25 23 23 23 25 25 25 26 25 26 24 24 24 3.5 4.5 5.9 3.7 4.5 5.9 3.5 4.5 5.8 3.5 4.4 5.7 education statistics). 4.9 4.6 4.5 : 4.6 4.5 4.6 4.5 : : : : 4.9 4.8 4.9 4.9 6.3 6.3 : : 5.6 5.7 : : 6.2 6.2 6.0 : 8.0 7.7 8.4 8.3 4.6 4.6 4.9 : Participation rates (16-18 year olds) by sex, 1998/99 Males Females 81 84 91 95 82 84 D: ISCED 6 missing. L: does not have a complete universitary system. ISCED 6 missing. Females per 100 males in tertiary education 1981/82 80 76 1997 107 102 1998/99 111 109 98 120 129 72 84 90 74 92 101 83 112 113 D: ISCED 6 missing. L: does not have a complete universitary system. ISCED 6 missing. Median age of students in tertiary education, 1998/99 Males and Females Males Females 23 24 23 21 22 21 26 26 26 26 27 25 20 20 20 22 23 22 D: ISCED 6 missing. L: 1997. Total public expenditure on education as a percentage of GDP (in PPS) 1998 5.0 5.2 8.2 4.7 1999 5.0 5.5 8.0 4.7 2000 5.1 : : : 2001 : : : : Source: Eurostat - UOE (Unesco. OECD and Eurostat questionnaires on 183 Annex II Statistical portraits data - European Union Member States 4 LABOUR MARKET EU-15 B DK D EL E F IRL I L NL A P FIN S UK 100 6.6 29.7 63.7 100 4.4 23.6 72.0 100 7.5 28.9 63.6 100 4.8 29.7 65.5 100 : : : 100 3.5 20.1 76.4 100 13.4 25.0 61.5 100 10.8 31.2 58.0 100 6.2 28.1 65.7 100 2.7 23.8 73.5 100 1.5 25.3 73.2 44.3 16.5 7.4 18.1 26.2 6.4 14.1 18.9 27.4 11.6 5.3 11.8 Persons in employment by sector (percentage share of total), 2000 Total Agriculture Industry Services 100 : : : 100 2.0 23.4 74.6 100 3.6 22.9 73.5 100 2.5 29.2 68.4 100 16.7 24.1 59.1 Percentage of persons in employment who are self-employed, 2000 Total 14.7 17.5 7.1 10.3 Part-time as a percentage of total employment, by sex, 2000 Total Males Females 17.7 6.2 33.2 20.8 5.8 40.5 21.3 10.2 34.1 19.4 5.0 37.9 4.5 2.5 7.8 8.0 2.8 16.9 16.7 5.3 30.8 16.4 6.9 30.1 8.4 3.7 16.5 10.4 1.9 24.9 41.0 19.3 70.4 14.3 3.9 28.3 10.8 6.2 16.3 12.3 8.0 17.0 22.6 10.6 36.0 25.0 9.1 44.6 Employment rates by age-group, 2000 50-54 70.0 61.0 55-59 51.9 37.9 60-64 22.6 12.4 65-69 6.5 2.3 70-74 2.9 1.8 80.8 72.6 30.9 8.1 : 74.3 56.4 19.6 4.9 2.3 61.8 48.2 31.3 11.2 3.7 58.4 46.0 26.4 3.9 1.0 74.9 48.1 10.2 2.1 0.9 64.4 53.1 35.8 14.7 7.7 58.1 36.5 18.0 6.0 2.7 66.4 38.9 14.5 3.4* : 71.4 54.1 18.5 5.1 2.9 72.1 42.4 12.1 5.5 2.8 71.9 58.3 45.2 27.1 18.8 80.1 58.5 22.8 5.0 2.9 83.8 78.6 46.0 14.2 5.6 76.1 63.2 36.1 11.3 4.8 10.3 12.8 16.5 12.8 29.8 32.0 10.4 14.9 8.5 4.6 5.2 10.1 3.4 5.3 7.6 13.8 : 8.1 18.3 20.4 : 16.3 : 13.9 5.2 7.0 30.6 34.2 14.1 16.0 3.6 5.9 8.7 12.2 4.5 6.6 11.4 16.9 7.4 9.0 18.8 22.3 12.8 19.7 11.5 16.2 6.2 8.0 Percentage of employees with a fixed-term contract 1990 2000 10.2 13.6 5.3 9.1 10.8 9.7 Percentage of employees with a fixed-term contract, by sex, 2000 Males Females 12.7 14.7 6.7 12.3 8.5 11.1 12.5 13.1 11.1 15.5 Average number of hours usually worked per week. full-time employees, by sex, 2000 Total Males Females 40.3 41.1 38.9 38.5 39.2 37.1 39.3 40.2 37.9 40.1 40.5 39.3 40.9 41.7 39.5 40.6 41.1 39.6 38.9 39.5 38.0 39.9 41.1 38.1 38.6 39.8 36.5 39.8 40.7 38.0 39.0 39.2 38.2 40.1 40.2 39.8 40.3 41.1 39.3 39.3 40.1 38.4 40.0 40.2 39.7 43.6 45.2 40.6 7.0 7.9 9.9 5.7 7.5 7.9 4.2 4.5 7.3 7.6 8.2 7.2 7.3 7.5 6.0 9.8 11.2 19.8 7.8 9.4 10.5 4.3 5.7 14.2 8.0 8.7 8.6 1.9 1.8 2.7 2.3 2.4 6.3 3.2 3.4 3.0 3.3 3.9 6.1 9.0 9.7 18.1 6.0 7.2 10.7 6.0 6.7 11.2 6894.8 143 64.4 1686.1 193.8 984.7 1097.2 43.9 1161.4 2.1 106.5 68.3 92.1 122.1 142.2 982.1 Unemployment rates, females 2000 9.7 1999 10.8 1994 12.7 8.8 10.5 12.9 5.3 6.0 9.3 8.3 9.1 10.1 16.7 17.6 13.7 20.6 23.0 31.4 11.5 13.2 14.5 4.2 5.5 14.6 14.4 15.6 15.6 3.3 3.4 4.1 3.8 4.6 8.3 4.4 4.7 4.9 5.1 5.2 8.0 10.6 10.7 14.9 5.8 7.1 7.8 4.9 5.3 7.5 168.3 70.3 1446.4 298.9 1395.2 1357.9 29.7 1304.3 2.4 132.2 74.1 118.6 130.8 122.2 648.2 9.8 10.8 19.3 7.0 8.7 10.2 3.4 4.5 12.3 11.5 12.4 12.7 2.4 2.4 3.5 3.5 3.5 7.6 2.8 2.6 2.9 3.5 3.7 6.5 10.9 10.9 17.7 5.4 6.5 13.3 9.4 10.2 13.8 13.1 14.2 19.4 7.3 8.5 11.4 3.3 4.0 9.0 12.0 12.6 12.4 2.6 2.5 3.2 4.6 6.2 6.4 3.0 3.5 4.2 4.8 4.9 7.0 11.4 10.8 13.3 5.7 6.6 10.0 7.2 7.1 8.4 Unemployment rates, males 2001 2000 1999 1994 Unemployment (1000). 2000 Unemployment (1000). 2000 7298.5 Youth unemployment/population ratio (aged 15-24), males 2000 1999 1994 7.7 8.5 11.1 5.9 8.7 8.7 5.0 6.7 7.8 5.3 5.3 5.0 Youth unemployment/population ratio (aged 15-24), females 2000 1999 1994 7.9 8.6 10.3 7.0 7.8 8.9 5.5 7.2 7.8 3.9 4.0 4.5 7.0 9.1 10.6 9.8 9.8 8.9 22.2 22.8 19.7 20.6 23.2 41.0 18.1 22.1 26.4 6.1 8.2 24.8 27.2 29.1 29.0 6.5 6.5 7.5 4.6 5.4 12.1 4.8 4.3 4.6 6.8 7.2 13.4 21.1 20.8 37.2 10.7 13.1 24.9 13.8 14.7 19.6 8.2 8.4 8.7 37.9 40.4 37.0 33.2 37.2 50.0 22.3 26.2 32.3 7.0 8.6 20.7 35.1 37.1 36.6 8.3 7.9 7.1 6.6 8.9 10.7 5.8 6.6 7.0 11.6 11.1 17.0 21.6 22.1 30.5 11.9 14.1 19.0 11.5 11.5 13.8 3.6 3.6 2.5 3.6 4.5 9.2 3.0 3.5 3.9 : : 9.7 4.9 5.4 5.1 0.5 0.7 0.9 0.7 1.1 3.2 0.9 0.9 : 1.5 1.5 2.6 2.4 2.3 : 2.0 2.4 : 2.0 2.3 5.7 10.2 10.5 7.8 9.6 11.7 18.7 4.7 5.2 5.5 : : 8.4 8.8 9.5 9.9 0.6 0.9 1.0 1.3 1.9 4.0 1.2 1.7 : 2.0 2.2 3.5 2.4 2.3 : 1.6 1.7 : 0.9 1.1 2.5 Youth unemployment rate (aged 15-24), males 2000 1999 1994 14.9 16.6 21.4 15.1 23.1 22.6 Youth unemployment rate (aged 15-24), females 2000 1999 1994 17.6 19.3 22.8 20.8 24.4 26.1 7.5 10.1 11.6 Long-term unemployment rate (12 months or more), males 2000 1999 1994 3.1 3.5 4.6 3.2 4.5 4.2 0.8 0.9 2.3 3.8 4.1 3.0 Long-term unemployment rate (12 months or more), females 2000 1999 1994 4.5 5.1 6.3 5.0 6.4 8.1 1.1 1.2 3.0 4.4 4.9 4.8 184 Statistical portraits data - European Union Member States Annex II 4 LABOUR MARKET (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK Persons unemployed for 12 months or more as a percentage ot total unemployed, 2000 Males Females 44 46 56 57 20 20 50 53 49.4 61.0 37 47 38 41 : : 61 61 26 19 32 34 29 27 47 40 27 22 33 28 34 19 7.4 7.6 12.1 : : 19.3 21.1 22.7 23.2 2.0 3.6 3.9 0.9 4.0 9.8 1.1 0.9 : 2.0 4.2 5.4 3.6 3.1 : 3.2 4.2 : 4.5 5.2 11.7 9.7 10.1 16.4 : : 14.9 28.0 29.2 30.8 1.5 2.5 3.4 1.8 8.1 8.8 2.3 2.8 : 5.7 5.5 8.1 2.5 2.2 : 3.1 3.0 : 3.1 3.1 6.4 23 39 29 49 17 12 30 26 32 27 Youth long-term unemployment rate (aged 15-24, 6 months or more), males 2000 1999 1994 7.4 8.8 13.8 8.1 14.2 15.5 0.3 1.1 3.5 4.6 4.9 3.9 14.2 15.0 12.9 10.3 12.3 27.3 Youth long-term unemployment rate (aged 15-24, 6 months or more), females 2000 1999 1994 9.5 10.3 14.7 11.4 13.7 17.7 0.6 2.1 3.7 4.1 4.7 4.9 28.7 31.0 28.5 18.8 23.7 38.2 Young persons unemployed for 6 months or more as a percentage of total young unemployed (aged 15-24), 2000 Males Females 49 54 53 55 4 8 47 50 64 76 50 57 41 44 : : 78 80 30.0 18.5 19 27 Employment rates represent persons in employment aged 15-64 as a percentage of the population of the same age. Persons in employment are those who during the reference week (of the Labour Force Survey) did any work for pay or profit for at least one hour or were not working but had jobs from which they were temporarily absent. Unemployed people - according to the International Labour Organisation (ILO) criteria are those persons aged 15 and over who are i) without work, ii) available to start work within the next two weeks and. iii) have actively sought employment at some time. Unemployment rates represent unemployed persons as a percentage of the active population of the same age. The active population is defined as the sum of persons in employment and unemployed persons. Source: Eurostat - Comparable estimates based on the European Union Labour Force Survey. 185 Annex II Statistical portraits data - European Union Member States 5 SOCIAL PROTECTION EU-15 B DK D EL E F IRL I L NL A P FIN S UK 21.6 22.9 25.5 26.4 21.2 21.9 20.2 20.1 28.4 31.0 30.2 29.7 19.6 17.8 14.8 14.1 25.2 24.8 25.3 25.2 22.5 24.0 21.8 21.0 32.6 30.1 28.0 27.4 27.0 29.5 28.8 28.7 17.2 21.2 22.6 22.7 29.8 31.6 26.7 25.2 34.3 34.7 32.9 32.3 25.7 28.1 26.5 26.8 3 713 6 748 4 748 5 943 9 235 7 004 7 396 3 675 5 925 7 367 6 048 Expenditure on social protection as a percentage of GDP 1991 1996 1999 2000 26.4 28.4 27.5 27.3 27.1 28.6 27.4 26.7 29.7 31.4 29.8 28.8 26.1 29.9 29.6 29.5 Expenditure on social protection in PPS per head of population, 2000 Total 6 155 6 458 7 754 7 025 4 032 Expenditure on social protection per head of population at constant prices (Index 1995 = 100) 1995 1996 1997 1998 1999 2000 100 102 103 104 107 109 100 102 103 105 107 107 100 100 99 100 102 102 100 104 103 105 108 108 100 105 111 120 132 143 100 102 102 104 107 110 100 101 102 104 106 107 100 101 107 110 117 121 100 102 108 108 111 113 100 104 107 109 116 118 100 100 101 101 102 105 100 101 102 104 109 111 100 99 105 115 123 127 100 102 101 100 100 100 100 99 99 101 104 105 100 103 105 106 108 114 Social benefits by group of functions (as a percentage of total social benefits) Old age and survivors’ benefits 1991 44.6 2000 46.4 Sickness, healthcare 1991 28.1 2000 27.3 Disability 1991 7.9 2000 8.1 Unemployment 1991 8.6 2000 6.3 Family and children 1991 7.8 2000 8.2 Housing and social exclusion n.e.c. 1991 3.0 2000 3.7 41.8 43.8 35.8 38.1 42.9 42.2 52.9 49.4 41.4 46.3 42.8 44.1 29.6 25.4 58.7 63.4 47.5 40.0 37.3 42.4 49.9 48.3 40.8 45.6 32.8 35.8 : 39.1 43.7 47.7 26.5 25.1 20.0 20.2 31.5 28.3 24.3 26.6 29.1 29.6 28.3 29.1 33.9 41.2 27.9 25.0 24.9 25.2 28.5 29.3 25.9 26.0 33.5 30.6 26.7 23.8 : 27.1 25.2 25.9 7.4 8.7 9.9 12.0 6.1 7.8 6.2 5.1 7.7 7.6 6.2 5.8 4.5 5.3 6.9 6.0 13.1 13.7 16.5 11.8 7.0 8.2 15.1 13.0 15.3 13.9 : 12.0 9.3 9.5 13.4 11.9 16.0 10.5 8.7 8.4 4.8 6.2 19.4 12.2 8.9 6.9 15.7 9.7 2.8 1.7 2.6 3.3 8.3 5.1 5.1 4.7 3.4 3.8 8.8 10.4 : 6.5 7.4 3.2 8.9 9.1 11.7 13.1 8.4 10.6 8.2 7.4 1.5 2.7 10.0 9.6 11.3 13.0 3.6 3.8 10.7 16.6 5.4 4.6 10.3 10.6 6.7 5.5 13.3 12.5 : 10.8 8.6 7.1 2.0 1.4 6.5 6.1 2.4 2.6 3.5 5.4 0.9 1.6 3.8 4.5 5.0 5.5 0.1 0.2 1.2 1.2 3.9 6.8 1.7 2.1 0.5 1.5 3.1 3.5 : 4.5 5.9 6.8 Social benefits by group of functions per head of population at constant prices (Index 1995 = 100) Total benefits 1996 102 1999 107 2000 109 Old age and survivors benefits 1996 102 1999 110 2000 112 Sickness, healthcare 1996 100 1999 106 2000 110 Disability 1996 103 1999 108 2000 109 Unemployment 1996 99 1999 90 2000 86 Family and children 1996 109 1999 116 2000 117 Housing and social exclusion n.e.c. 1996 102 1999 110 2000 113 102 107 107 100 102 102 104 108 108 104 132 143 102 107 110 102 107 107 101 116 121 103 111 113 104 116 118 100 101 104 101 109 111 99 119 126 101 100 100 99 104 105 103 108 115 101 108 108 103 103 103 102 106 107 106 132 136 104 112 116 102 108 109 98 111 116 102 112 113 101 105 104 104 112 116 102 109 111 106 129 138 105 108 109 104 109 109 105 116 127 106 112 113 100 112 116 100 98 99 100 124 146 103 111 114 101 106 110 98 129 137 103 113 122 109 117 119 97 104 107 100 112 113 87 109 109 104 110 113 100 120 130 102 115 123 101 105 105 101 116 115 110 123 123 104 132 152 105 112 114 103 107 107 106 121 133 104 99 96 104 134 127 97 95 98 105 117 121 105 122 137 100 95 93 96 101 104 99 97 100 101 101 98 94 77 73 105 105 101 97 168 195 90 83 81 103 100 94 102 84 76 94 78 63 113 94 125 101 61 54 105 101 94 107 84 89 99 79 72 94 77 62 90 66 65 101 112 111 100 107 108 132 150 152 102 112 120 120 140 150 100 105 104 111 126 132 112 129 135 103 140 149 96 95 103 98 98 104 100 119 133 95 96 94 94 95 99 103 96 91 99 56 56 95 91 91 104 98 96 111 191 204 126 125 109 101 110 109 106 121 127 112 160 156 102 106 120 97 109 109 104 139 161 117 494 467 102 102 97 95 80 75 106 103 104 Receipts of social protection by type (as a percentage of total receipts) General government contributions 1991 30.9 21.4 2000 35.8 25.3 Employers' social contributions 1991 41.4 43.7 2000 38.3 49.5 Social contributions paid by protected persons 1991 23.6 25.7 2000 22.4 22.8 Other receipts 1991 4.1 9.2 2000 3.5 2.5 81.7 63.9 26.9 32.5 32.8 29.1 27.3 26.9 17.6 30.6 60.0 58.3 29.1 39.8 40.6 47.1 23.9 14.2 35.7 35.3 26.1 38.7 44.1 43.1 : 46.7 44.6 47.1 7.2 9.1 42.2 36.9 38.1 38.2 53.2 52.7 50.4 45.9 24.0 25.0 52.6 43.2 29.8 24.6 20.1 29.1 38.1 37.1 41.8 35.9 40.9 37.7 : 39.7 27.9 30.2 4.5 20.3 28.3 28.2 20.3 22.6 16.7 16.4 28.3 20.6 15.0 15.1 16.1 14.9 22.1 23.8 40.3 38.8 25.1 26.8 19.1 17.6 7.2 12.1 : 9.4 25.8 21.4 6.6 6.7 2.6 2.4 8.8 10.1 2.7 4.0 3.6 2.9 1.0 1.5 2.2 2.1 7.5 4.5 15.7 17.9 1.2 0.8 13.0 7.8 7.8 7.1 : 4.3 1.7 1.3 186 Statistical portraits data - European Union Member States Annex II 5 SOCIAL PROTECTION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK Receipts of social protection by type per head of population at constant prices (Index 1995 = 100) Total receipts 1996 102 106 1999 109 114 2000 111 114 General government contributions 1996 102 103 1999 118 112 2000 121 110 Employers' social contributions 1996 101 107 1999 107 115 2000 110 115 Social contributions paid by protected persons 1996 103 107 1999 102 115 2000 103 117 Other receipts 1996 102 102 1999 102 93 2000 101 98 100 103 104 103 109 109 102 125 139 101 114 121 102 110 112 101 120 127 103 112 114 103 115 122 100 109 113 101 108 110 109 122 128 102 100 100 100 103 109 103 109 113 98 97 95 110 125 124 100 124 139 96 105 108 104 155 159 101 114 118 100 144 151 104 115 123 99 95 94 99 106 108 123 146 155 99 95 94 95 103 104 101 101 106 101 94 93 98 100 100 106 126 142 104 117 128 101 108 108 100 130 142 104 96 98 105 110 117 101 149 156 102 108 109 98 120 128 105 112 112 105 100 116 104 120 135 112 144 153 104 107 107 99 122 133 103 112 117 104 81 83 102 127 137 102 95 98 100 129 133 99 96 102 103 111 112 100 121 127 100 92 88 124 179 194 105 112 105 101 104 110 110 93 96 96 128 139 109 165 181 92 88 90 109 165 229 111 149 101 93 88 106 101 107 105 102 124 135 119 76 69 106 96 103 92 65 59 98 145 165 The 2000 data is provisional for B, D, EL, E, F, I, NL, P, FIN, S and UK. No data on benefits and receipts for S for the years 1991 and 1992. EU-15 data for 1991 are therefore estimated. The abbreviation 'n.e.c.' indicates not elsewhere classified. Source: Eurostat - European system of integrated social protection statistics (ESSPROS). Total public expenditure on LMP measures as a % of GDP Categories 2-7 (active) excl. sub category 2.4. 1998* 1999 2000 : 0.733 0.681 1.109 1.026 1.000 1.628 1.804 1.641 0.910 1.004 0.917 : 0.258 0.253 0.511 0.649 0.632 0.901 0.964 0.931 0.924 0.861 0.929 : 0.415 0.436 : : : : 0.915 0.920 0.292 0.368 0.365 : 0.247 0.254 0.971 0.907 0.742 2.260 1.998 1.507 0.061 0.089 0.089 Sub-category 2.4 1998 1999 2000 0.066 0.074 0.075 - 0.015 0.026 0.026 0.045 0.059 0.061 0.045 0.011 0.016 - 0.112 0.104 0.109 0.024 0.021 0.018 0.094 0.030 0.128 0.032 0.135 0.036 0.040 0.038 0.040 0.039 0.050 0.033 0.066 0.087 0.098 0.044 0.034 0.023 - 0.100 0.106 0.104 Categories 8-9 (passive) 1998 1999 2000 : 1.452 1.282 2.514 2.371 2.178 2.936 2.567 2.378 2.302 2.152 1.924 : 0.648 0.449 1.664 1.477 1.393 1.566 1.534 1.401 1.490 1.108 0.786 0.755 : 0.656 0.512 0.611 0.439 2.412 2.143 1.890 1.430 1.335 1.204 : 0.850 0.876 2.575 2.362 2.093 1.902 1.738 1.409 0.628 0.555 0.434 Total 1998 1999 2000 : 2.257 2.037 3.623 3.397 3.177 4.579 4.397 4.045 3.257 3.214 2.901 : 0.917 0.718 2.175 2.126 2.025 2.579 2.602 2.441 2.439 1.990 1.733 : 1.200 1.182 : 3.095 2.850 1.761 1.753 1.602 : 1.184 1.228 3.590 3.303 2.859 4.161 3.736 2.916 0.789 0.750 0.627 Source: Eurostat - Labour Market Policy Database (LMP) 187 : : : Annex II Statistical portraits data - European Union Member States 6 INCOME, POVERTY AND SOCIAL EXCLUSION EU-15 B DK D EL E F IRL I L NL A P FIN S UK 10688 22084 15235 14865 8529 11656 12324 15701 Mean equivalised net annual income, 1998 PPS 13420* 17235 15197 15150 9238 9822 14092 13025 Share of income by quintile. 1998 Total 100 Bottom quintile 8 2nd quintile 13 3rd quintile 17 4th quintile 23 Top quintile 39 100 8 12 16 21 43 100 12 14 19 22 33 100 8 14 18 22 39 100 6 12 16 23 42 100 6 12 17 23 41 100 8 13 18 23 38 100 8 11 15 22 43 100 7 13 18 24 39 100 9 13 17 23 38 100 9 13 17 22 39 100 10 14 18 22 36 100 6 11 16 22 45 100 11 15 17 22 34 100 10 15 18 23 35 100 7 12 17 23 41 102 99 103 97 102 98 101 99 101 98 104 97 103 99 103 97 102 99 104 96 94 79 108 113 94 91 96 114 116 77 86 90 108 111 100 86 91 110 104 97 87 84 107 119 92 88 103 106 110 87 88 100 114 113 76 95 91 107 111 89 92 90 101 129 91 85 98 114 127 69 Median equivalised income of all persons by sex (indexed. total = 100). 1998 Males Females 102* 98* 102 99 103 97 102 98 102 98 101 99 Median equivalised income of all persons by age (indexed total = 100), 1998 Children below 16 16-24 25-49 50-64 65 and over 88* 90* 109* 114* 90* 95 85 111 108 84 95 86 110 116 74 83 89 107 111 97 100 97 116 102 76 91 92 110 107 96 Median equivalised income of all persons by type of household (indexed total = 100), 1998 1 adult living alone 88* 86 ... 1 male adult 106* 98 ... 1 female adult 80* 77 Single-parent with dependent children 73* 68 2 adults aged 15-64 without dependent children 132* 122 2 adults. at least one aged 65 or more. without dependent children 96* 86 2 adults with one dependent child 112* 117 2 adults with two dependent children 100* 104 2 adults with three or more dependent children 70* 74 80 91 71 93 101 88 89 116 75 83 119 76 93 98 87 64 83 57 100 127 90 111 129 96 91 107 83 90 115 79 66 91 64 77 82 77 83 89 77 70 95 62 89 61 110 77 77 64 89 79 66 74 77 87 78 62 123 127 119 131 124 162 135 120 135 129 132 118 137 145 78 104 81 98 101 85 102 98 99 94 73 97 109 80 122 105 120 112 114 128 115 104 109 103 120 116 117 116 108 93 113 98 112 112 95 100 90 90 106 108 104 99 86 55 86 106 69 82 52 87 79 74 53 90 87 75 Median equivalised income of all persons aged 16 and over by level of educational attainment (indexed total = 100), 1998 Less than upper secondary Upper secondary Tertiary education 89* 108* 140* 80 102 132 84 108 123 88 106 127 82 121 182 90 116 163 90 91 115 84 123 164 93 125 162 90 120 163 102 96 127 85 108 143 93 134 260 92 100 131 91* 103 120 83 100 125 18 18 17 17 16 19 20 19 20 12 12 12 12 11 12 13 11 15 20 19 22 8 8 8 10 10 10 21 19 24 22 28 13 15 18 23 16 14 12 24 28 25 18 17 16 17 18 9 10 9 17 24 10 6 6 16 12 10 10 21 27 16 15 17 34 6 19 7 6 8 11 25 10 4 7 26 22 14 13 40 At risk of poverty rate (60% of median equivalised income), by sex, 1998 Total Males Females 18* 17* 19* 16 14 17 9 7 10 16 15 16 22 21 22 19 19 19 At risk of poverty rate (60% of median equivalised income), by age, 1998 Children below 16 16 - 24 25 - 49 50 - 64 65+ 24* 23* 14* 14* 20* 18 22 11 16 20 3 15 5 4 27 26 23 11 13 13 21 21 16 22 36 25 24 17 17 14 At risk of poverty rate (60% of median equivalised income) for persons aged 16 and over. by most frequent activity status, 1998 Employed, excluding self-employed Self-employed Unemployed Retired Other economically inactive 7* 16* 38* 18* 27* 2 10 34 17 29 3 7 5 23 20 6 6 38 14 27 10 23 36 36 24 7 28 38 12 22 8 20 40 16 31 4 8 41 20 25 7 18 48 13 25 5 12 : 11 15 6 17 21 3 14 5 22 32 14 22 9 31 31 28 22 2 13 17 7 17 : : : : : 7 13 38 38 33 At risk of poverty rate (60% of median equivalised income), by type of household, 1998 1 adult without dependent children 25* ... Male 20* ... Female 27* 2 adults without dependent children ... both younger than 65 9* ... at least one aged 65 or more 16* 3 or more adults without dependent children 9* Single-parent with dependent children 35* 2 adults with dependent children ... 1 child 11* ... 2 children 13* ... 3 or more children 41* 3 or more adults with dependent children 22* 20 13 24 27 18 36 23 22 24 30 19 36 11 10 12 22 22 22 45 33 57 21 15 24 12 5 17 15 16 14 24 12 30 44 36 48 20 20 19 20 19 20 40 27 48 9 5 8 15 13 11 10 11 10 5 7 17 8 4 7 21 18 8 34 17 13 8 13 9 6 17 35 3 3 29 6 3 8 16 11 9 4 13 2 7 6 10 6 : 8 25 15 47 13 38 31 48 18 27* 43 32 40 9 19 45 7 12 34 6 3 0 8 12 56 10 13 20 16 22 29 11 8 40 15 11 32 12 15 54 8 9 22 9 9 23 11 11 32 11 13 53 5 4 8 5 6 14 15 14 34 13 0 11 37 25 33 13 36 17 15 10 21 4 : 17 188 Statistical portraits data - European Union Member States Annex II 6 INCOME, POVERTY AND SOCIAL EXCLUSION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK 86 70 75 88 89 89 : 78 Percentage of the population in households which have difficulties in making ends meet, 1998 82* 77 87 : 87 85 78 82 See methodological notes under Income distribution and regional cohesion (3.14). Source: Eurostat - European Community Household Panel (ECHP). UDB December 2001 version. L: 1996. FIN: 1997. 189 Annex II Statistical portraits data - European Union Member States 7 GENDER EQUALITY EU-15 B DK D EL E F IRL I L NL A P FIN S UK 5 393 85 21.6 14 374 113 30.2 16 1970 605 30.7 . . . . 19 1180 359 30.4 22 1693 437 25.8 . . . . 20 933 78 8.4 . . . . 10 761 208 27.3 9 448 117 26.1 2 111 13 11.7 . . . . 23 1717 810 47.2 3 260 71 27.3 Women in regional parliaments, 2000 Number of regions 143 Number of members 9840 Number of female members 2896 Percentage of female members 29.4 EL, IRL, L, FIN: No elected regional parliaments existing. F: 1999 data; With "Assemblée territoriale de Corse". I: From some regions no data is available. P: Only the autonomous regions of Açores and Madeira have regional parliaments. Women in regional governments (including junior ministers), 2000 Number of regions 97 Number of members 940 Number of female members 206 Percentage of female members 21.9 5 37 8 21.6 . . . . 16 183 44 24.0 . . . . 19 177 31 17.5 . . . . . . . . 20 194 15 7.7 . . . . . . . . 9 76 17 22.4 2 16 0 0.0 . . . . 23 224 81 36.2 3 33 10 30.3 DK, EL, F, IRL, L, FIN: No regional governments existing. D: In some regions junior ministers no longer belong to the government and are no longer included. F: 1999 data. I: from some regions no data is available. NL: Regional governments are appointed. P: Only the autonomous regions of Açores and Madeira have regional governments. S: Some regions do not have governments. Women in local councils. 1997 Number of seats Number of seats occupied by women Percentage of seats occ. by women 364 367 12 912 4 658 177 193 : : : 883 94 886 1 105 72 343 19.9 11 072 7 508 7 337 2 565 1 261 30 973 : : : 103 18 237 19.9 27.1 17.5 : : : 11.7 19.2 12 482 11 006 23 325 114 2 475 929 1 057 3 932 4 533 6 164 10.3 22.4 12.4 14.4 31.5 41.2 26.4 Local data are incomplete. Due to the huge differences in local level political decision-making data provided are not always comparable. D: No data available for Saxony-Anhalt and Mecklenburg-Vorpommern. A: Only data from Styria available. Source: European database - Women in decision making (www.db-decision.de). 190 Statistical portraits data - European Union Member States Annex II 8 HEALTH AND SAFETY EU-15 B DK D EL E F IRL I L NL A P FIN S UK Infant mortality rate, per 1000 live births 1970 23.4 21.1 2000 4.9 5.2 14.2 5.3 22.5 4.4 29.6 6.1 28.1 4.6 18.2 4.6 19.5 5.9 29.6 5.1 24.9 5.1 12.7 4.8 25.9 4.8 55.5 5.5 13.2 3.8 11.0 3.4 18.5 5.6 71.2 74.5 77.3 79.3 69.6 74.7 76.1 80.7 72.2 75.5 76.8 80.6 72.5 75.5 78.6 82.7 70.2 75.0 78.4 82.5 70.1 74.2 75.6 79.2 70.6 76.3 77.4 82.4 69.1 74.9 75.9 81.3 72.7 75.5 79.3 80.5 69.0 75.4 76.1 81.2 67.7 72.7 75.2 79.7 69.2 74.2 77.6 81.0 72.8 77.4 78.8 82.0 70.2 75.4 76.2 80.2 Source: Eurostat - Demographic Statistics. Life expectancy at birth 1980, males 2000, males 1980, females 2000, females 70.5 75.3 77.2 81.4 70.0 74.6 76.8 80.8 D. EL and F: 1999. Source: Eurostat - Demographic Statistics. Life expectancy with severe disability at 16 years of age, by sex, 1996 Males Females 4 5 4 5 3 5 3 3 4 5 4 5 6 8 2 3 3 5 4 5 4 6 6 7 4 5 7 9 : : 5 6 62 62 63 69 67 70 65 68 60 63 64 67 67 70 61 64 63 63 62 66 59 61 56 59 : : 61 62 Disability-free life expectancy (at birth), by sex, 1996 Males Females 63 66 65 69 Percentage of persons aged 16 and over stating that they are hampered in daily activities by any physical or mental health problem, illness or disability by sex, 1998 Total 26 22 23 40 16 16 25 16 13 : 23 17 24 29 : : Males 23 19 19 37 15 15 23 15 11 : 20 16 21 28 : : Females 28 25 27 43 18 18 26 18 15 : 26 19 27 31 : : Percentage of persons aged 65 and over that they are hampered in daily activities by any physical or mental health problem, illness or disability by sex, 1998 Total Males Females 52 50 54 44 42 45 45 42 48 71 73 71 39 38 40 38 33 42 54 54 56 37 29 43 34 32 35 : : : 41 37 45 43 38 45 52 46 55 62 61 62 : : : : : : 9 20 71 : : : 14 : : 24 28 48 28 34 38 : : : 31 : : Percentage of persons aged 16 and over with an above-mentioned problem/illness and who are hampered in their daily activities, 1998 Yes, severely Yes, to some extent No 10 16 74 15 7 88 7 16 77 11 29 60 8 9 83 7 10 83 12 13 75 3 13 84 5 8 87 : : : 8 15 77 6 12 82 10 14 76 Percentage of persons aged 65 and over with an above-mentioned problem/illness and who are hampered in their daily activities, 1998 Yes, severely Yes, to some extent No 24 29 37 31 13 56 20 25 55 25 46 29 21 18 61 16 22 62 29 26 45 8 29 63 16 18 66 : : : 18 23 59 18 25 57 Percentage of the population aged 16 and over who feel that their health is bad or very bad, by level of education, 1998 Pre-primary, primary and lower secondary education Upper secondary education Total tertiary education 16 8 6 9 4 2 13 5 3 23 18 16 14 3 2 17 3 2 9 3 3 5 1 1 18 4 2 : : : 5 2 1 13 5 3 27 6 6 : 7 3 : : : 15 9 7 4 3 6 7 6 9 22 19 26 8 7 10 : : : 10 9 11 9 6 11 23 19 25 55 48 61 24 19 27 : : : 16 14 17 409 208 345 190 351 236 Percentage of the population aged 16 and over who feel that their health is bad or very bad, by sex, 1998 Total Males Females 12 11 14 6 4 7 7 6 7 19 17 21 9 8 11 11 9 13 9 8 11 3 3 4 12 10 14 : : : Percentage of the population aged 65 and over who feel that their health is bad or very bad, by sex, 1998 Total Males Females 28 24 30 12 10 14 17 18 16 36 30 40 27 25 28 31 25 35 22 22 22 9 6 11 36 33 38 : : : FIN: 1997, EU-15 without L, FIN and S. Source: Eurostat - European Community Household Panel (ECHP). UDB December 2001 version. Standardised death rates (SDR) per 100 000 population by sex, 1999 Males Diseases of the circulatory system Cancer Diseases of the respiratory system External causes of injury and poisoning Females Diseases of the circulatory system Cancer Diseases of the respiratory system External causes of injury and poisoning 325 248 328 301 374 268 388 243 368 217 266 260 252 289 410 248 321 256 328 238 314 270 414 232 394 243 83 114 90 62 44 116 69 158 60 92 100 48 133 90 54 141 59 82 72 51 60 56 88 58 54 72 39 72 73 115 53 40 207 139 207 155 220 201 250 147 293 117 179 112 136 126 251 167 208 132 203 135 185 162 282 140 282 122 219 122 205 137 214 165 42 40 65 28 29 47 32 103 23 42 49 23 61 40 33 95 23 34 34 20 19 18 38 21 21 30 19 25 22 34 23 17 B: 1995, DK: 1996, EL: 1997, F and I 1998. Source: Eurostat - Health and safety statistics. 191 Annex II Statistical portraits data - European Union Member States 8 HEALTH AND SAFETY (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK 810 716 567 440 1034 920 507 489 427 413 977 834 619 485 723 487 1182 562 583 497 786 712 558 480 919 761 1249 374 592 413 1426 2592 2447 1414 3970 1046 3971 2983 1798 Hospital beds per 100 000 inhabitants 1990 1999 779 630 Source: Eurostat - Health and safety statistics. Number of persons per 100 000 discharged from hospitals by ICD diagnosis. 2000 Diseases of the circulatory system External causes of injury and poisoning Diseases of the respiratory system Cancer Mental and behavioural disorders Infectious and parasitic diseases 2420 2351 2640 3369 1952 1292 2386 1646 : 1896 1995 : 850 2151 : 1624 : 744 2960 : 2169 : 1653 1427 1367 : 976 264 1559 1037 1815 330 1229 262 625 508 1224 108 675 463 1043 1102 1485 129 774 1507 2871 112 507 1838 1869 1051 1441 370 1791 655 1440 1598 1266 1073 1036 1461 1445 1239 2135 639 2099 718 2373 1193 1184 394 389 464 365 374 186 448 407 311 347 119 359 200 725 458 257 EL. E. L and S 1998; EU-15. D. I. A and P: 1999. UK includes only England. Source: Eurostat - Health and safety statistics. Prevalence per 1000 for Alzheimer and other dementias. 2000 12.3 12.6 12.4 12.6 12.5 12.4 12.6 8.4 13.7 10.7 10.4 12.0 10.4 11.4 14.9 12.4 6.6 7.7 8.6 9.5 6.6 6.7 8.0 8.1 6.1 6.0 8.0 8.1 7.1 8.0 6.2 8.2 7.9 6.6 8.5 7.9 6.0 7.3 105 107 108* : 99 98 92 83 91 94 107 108 106 97 Source: Alzheimer Europe and Eurostat Total expenditure on health (percentage of Gross Domestic Product) 1990 2000 7.9 8.0 7.4 8.7 8.5 8.3 8.7 10.3 7.5 8.3 D. L and S: 1999. Source: OECD Health data 2001. Work accidents per 100 000 employed persons by selected type of activity. 1999. Index (1998 = 100) Total Construction Agriculture. hunting and forestry Transport. storage and communication Manufacturing Hotels and restaurants Wholesale and retail trade; repairs 100 98 96 110 95 104 99 98 93 92 107 104 101 93 90 112 99 100 104 76 171 117 81 98 107 86 100 117 : 98 47 107 100 117 97 100 103 84 97 114 114 85 160 94 97 97 113 105 98 103 98 107 102 99 105 83 82 218 102 98 95 121 101 106 : : : 107 96 110 93 114 82 108 90 79 103 106 120 102 106 128 102 90 126 99 82 109 102 151 102 107 : 103 88 82 112 112 Work accidents per 100 000 employed persons by selected type of activity. 1999 Total Construction Agriculture. hunting and forestry Transport. storage and communication Manufacturing Hotels and restaurants Wholesale and retail trade; repairs 4 088 7 809 4 924 9 508 3 031 4 062 4 908 9 659 2 740 6 247 7 027 14 901 4 991 11 409 1 291 2 122 4 067 4 973 6 440 10 743 4 223 2 721 3 301 6 311 5 048 8 370 3 137 7 074 1 425 2 430 1 606 2 367 7 060 5 194 2 056 13 825 2 500 3 152 5 175 5 003 9 341 8 985 7 133 11 678 2 682 825 1 450 2 474 5 702 4 471 3 711 4 820 4 591 4 594 3 886 5 011 2 224 11 000 4 639 5 339 2 275 4 034 1 057 6 404 3 152 6 187 6 276 4 412 5 596 1 589 1 335 948 5 613 4 427 4 889 5 211 3 088 4 130 3 179 5 741 1 730 2 942 3 637 1 318 3 929 6 733 2 760 3 954 4 158 2 023 1 596 1 777 1 209 1 781 1 779 1 993 2 496 3 682 1 502 2 357 1 763 4 950 3 762 572 1 997 3 458 2 469 1 518 4 206 1 831 1 083 1 452 : : 100 99 96 75 93 90 108 103 106 109 Work accidents per 100 000 employed persons by sex. 1999. Index (1998=100) Males Females 100 101 96 96 93 103 99 99 96 88 107 109 101 106 87 106 99 102 107 99 NL: break in time series (based on 1994 data. revalued in 1999 in proportion to the evolution 1999/1994 of the number of persons in employment in NL. Work accidents per 100 000 employed persons by sex. 1999 Males Females 5 280 1 909 6 215 2 116 3 673 1 804 6 539 2 109 3 654 979 8 632 3 499 6 575 2 277 1 706 629 4 932 6 384 2 093 1 956 : : 4 401 1 493 7 042 1 852 4 101 1 428 1 674 907 1 971 954 2 1 1 1 1 2 2 2 2 1 417 262 321 258 115 895 1 055 551 649 431 396 438 1 307 848 772 580 591 558 7 6 5 3 3 184 84 63 Only those working accidents that lead to more than 3 days absence are included. Source: Eurostat - Health and safety statistics. Number of persons killed in road accidents 1970 1980 1990 1999 2000 2001 73 59 51 42 41 229 600 711 131 116 : 2 2 1 1 1 950 396 976 397 470 : 1 208 690 634 514 501 415 21 15 11 7 7 6 332 050 046 772 503 961 1 1 2 2 1 931 225 737 116 074 882 4 5 6 5 5 5 197 017 948 738 776 193 15 12 10 8 8 8 034 384 289 487 079 100 540 564 478 414 415 410 137 106 10 8 6 6 6 208 537 621 633 410 : 132 98 71 58 70 64 111 144 3 1 1 1 1 1 181 997 376 090 160 065 238 742 391 079 976 955 499 239 402 564 580 : Number of persons killed in road accidents per million inhabitants 2001 104 143 77 85 178 129 66 117 For road accidents. 'persons killed' are all those killed within 30 days of the accident. For Member States not using this definition. corrective factors were applied. B, I and UK: 2000 data. Source: Eurostat - Transport Statistics. 192 60 Statistical portraits data - European Union Member States Annex II 9 CONSUMPTION EU-15 B DK D EL E F IRL I L NL A P FIN S UK 62 121 12 050 13 610 57 99 10 990 11 140 47.4 48.6 976 16 350 886 14 850 63.0 More statistical data on consumption can be found in "Consumers in Europe – Facts and figures 1996-2000". Eurostat. 2001. ISBN 92-894-1400-6. Final consumption expenditure of households, 2000, current prices Thousand millions of euro Euro per inhabitant Thousand millions of PPS PPS per inhabitant Percentage of GDP 4561 12 090 4561 12 090 56.9 131 12 790 134 13 070 52.8 83 15 510 68 12 730 46.9 1144 13 920 1092 13 290 56.5 83 7 870 106 10 080 70.8 356 8 920 423 10 710 58.5 760 12 580 728 12 040 54.1 47 12 490 46 12 240 45.7 699 8 12 110 17 700 792 7 13 730 16 329 60.0 38.0 197 12 380 206 12 930 49.1 113 13 950 110 13 570 55.2 69 6 930 102 10 220 60.2 EU-15, EL: 1999. The "per inhabitant" figures are forecasts for EU-15, D, EL, IRL, PT and UK. Source: Eurostat. National Accounts - ESA95 - aggregates (theme2/aggs) Structure of household consumption expenditure, 1999 (%) Total 100 Food and non-alcoholic beverages : Alcoholic beverages and tobacco : Clothing and footwear : Housing. water. electricity. gas and other fuels : Furnishings. household equipment & routine maintenance : Health : Transport : Communication : Recreation and culture : Education : Restaurants and hotels : Miscellaneous goods and services : 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 13.3 13.1 11.1 16.6 18.3 16.2 15.4 19.0 10.1 10.5 13.4 21.2 14.2 15.4 10.5 2.3 5.4 4.2 5.5 2.8 5.7 3.5 8.6 2.7 7.4 2.7 5.6 7.7 6.2 1.9 7.5 2.0 5.9 2.1 6.0 2.6 6.6 2.8 6.3 2.9 4.6 2.9 5.2 3.0 5.5 26.2 28.4 31.2 21.9 27.5 23.2 17.4 24.7 27.4 26.7 23.9 19.9 28.1 26.8 28.3 6.5 4.7 12.5 2.2 10.7 0.5 5.7 6.4 2.4 14.1 2.1 11.2 0.4 4.1 7.4 3.6 13.3 2.5 11.9 0.5 4.9 7.5 6.3 11.2 3.3 4.5 2.4 8.8 5.0 2.5 12.5 2.0 6.2 1.4 9.2 7.6 5.2 14.5 2.0 7.6 0.5 6.9 4.5 1.6 13.0 2.5 9.1 1.4 5.1 7.6 4.4 13.7 2.5 6.3 0.8 4.6 8.2 2.4 15.4 2.1 8.7 0.1 9.6 7.2 1.1 10.3 2.2 10.4 1.2 7.0 7.2 2.4 14.4 2.6 12.3 0.3 5.4 6.7 4.6 15.7 2.0 3.7 1.3 9.2 4.5 3.7 17.0 2.8 10.7 0.2 4.1 5.0 3.0 13.4 2.6 14.6 0.1 3.8 7.3 1.1 13.6 2.3 13.4 1.3 7.9 10.0 8.1 5.0 5.5 5.1 8.1 8.1 7.1 8.0 15.3 8.9 6.5 7.1 7.2 5.8 F, P: 1994. Source: Eurostat - Household Budget Survey (theme3/hbs) Average number of rooms per person 1981/82 1.6 1998 1.9 1.8 2.1 1.6 2.0 1.7 1.9 1.2 1.4 1.3 1.8 1.6 2.0 1.3 2.1 1.3 1.6 1.9 2.2 1.8 2.6 : 2.0 1.0 1.6 1.3 1.7 1.7 2.0 1.8 2.3 Households owning their accommodation (%) 1981/82 54 58 1990/91 59 65 1998 59 71 55 54 56 40 39 41 70 76 74 73 78 82 51 54 53 74 79 75 59 68 71 60 65 70 42 45 51 48 50 51 57 65 66 61 67 64 59 56 59 56 66 69 Source: Eurostat - Censuses of Population (1981/82. 1990/91). European Community Household Panel (1998). L: 1996. FIN: 1997. S: National sources for 1981/82 and 1990/91. Percentage of households possessing selected consumer durables, 1998 Colour television Video recorder Microwave oven Dishwasher 97 67 51 33 96 68 60 32 97 72 41 39 97 64 52 45 96 47 12 23 99 67 46 22 94 65 55 36 98 76 66 26 97 59 18 25 98 68 33 56 98 73 67 29 97 65 56 49 93 57 27 23 94 61 74 42 98 68 66 41 98 83 77 23 97 100 90 87 93 83 91 96 81 98 99 94 99 100 95 97 99 92 81 95 59 95 100 85 : : : 96 99 92 70 14 16 76 3 21 83 4 14 68 5 27 74 5 21 63 20 17 65 9 26 72 : : 70 : : Percentage of households possessing a telephone. by income group, 1998 Total Top income group Bottom income group 95 98 86 95 99 85 98 100 95 96 97 86 95 99 85 89 97 77 Percentage of households possessing a car or a van (available for private use), 1998 Have a car Cannot afford one Don't want one 73 4 23 76 6 18 63 14 24 73 : : 57 19 24 67 12 21 80 7 13 L: 1996. FIN: 1997. It doesn't matter whether the item (in the three tables above) is owned. rented ot otherwise provided for use. Top income group refers to household income that is 140% or more of national median income. Bottom income group refers to household income that is less than 60% of national median income. Source: Eurostat - European Community Household Panel (ECHP). UDB December 2001 version. 193 Annex II Statistical portraits data - European Union Member States 9 CONSUMPTION (Contd.) EU-15 B DK D EL E F IRL I L NL A P FIN S UK Level of internet access - households - Percentage of households who have Internet access at home 2000 2001 2002 18.3 36.1 40.4 20.2 34.7 40.9 45.3 58.9 64.5 13.6 37.9 43.7 5.8 11.7 9.2 9.6 23.4 29.5 12.9 26.2 35.5 17.5 46.2 47.9 19.2 32.9 35.4 26.9 43.6 55.0 46.1 58.5 65.5 16.9 46.2 49.1 8.4 23.4 30.8 28.2 48.1 53.7 47.5 64.3 64.2 24.4 46.5 45.0 2.35 2.38 2.47 2.37 1.80 2.01 2.21 2.36 : 4.30 4.90 : 3.96 4.83 5.20 5.37 2.73 3.30 3.52 3.73 1.24 1.73 1.86 1.99 2.93 3.89 4.34 4.46 4.37 6.24 6.48 6.87 4.43 4.82 5.15 5.53 1.7 2.4 2.5 2.7 : 2.3 2.7 : 2.2 2.7 2.8 3.1 2.1 2.0 2.1 2.3 1.2 3.2 3.3 3.6 1.6 2.3 2.4 2.3 2.9 2.6 2.7 2.8 2.5 2.6 2.7 2.9 Information Technology expenditure as a % of GDP (hardware. software and services) 1992 1998 1999 2000 3.03 3.57 3.90 4.15 3.38 3.97 4.33 4.55 3.94 4.77 5.04 5.35 2.94 3.62 3.95 4.22 0.71 1.00 1.09 1.20 1.62 1.78 1.85 1.96 3.59 4.09 4.33 4.67 Communications expenditure as a % of GDP (telecommunication equipment and services) 1992 1998 1999 2000 2.1 2.4 2.5 2.7 1.8 2.4 2.5 2.7 2.1 2.3 2.4 2.4 2.2 2.2 2.3 2.5 1.5 3.2 3.5 3.8 2.0 2.2 2.3 2.5 2.0 2.2 2.3 2.6 Source: Eurostat - Information Society Statistics 194 2.7 3.0 3.0 3.0 Key social indicators per acceding/candidate country Annex III Annex III: Key social indicators per acceding/candidate country Nr. Key indicator Unit Year EU-15 BG 3 Old age dependency ratio % 2001 24.3° 24.0 4 Net migration rateper 1000 inhab. 2000 3.1° 0.0 5t Early school-leavers not in further education or training - total % 2001 19.4 20.3 5m Early school-leavers not in further education or training - males % 2001 21.9 21.1 5f Early school-leavers not in further education or training - females % 2001 16.8 19.5 6t Lifelong learning - total % 2001 8.4 : 6m Lifelong learning - males % 2001 7.9 : 6f Lifelong learning - females % 2001 8.9 : 7 Employment rate (cf. nrs 19m & 19f) % 2001 64.0 49.6 8at Employment rate of older workers - total % 2001 38.6 23.9 8am Employment rate of older workers - males % 2001 48.7 34.2 8af Employment rate of older workers - females % 2001 28.9 14.7 8t Effective average exit age - total years 2001 59.9 : 8m Effective average exit age - males years 2001 60.5 : 8f Effective average exit age - females years 2001 59.1 : 9t Unemployment rate - total % 2001 7.4 19.6 9m Unemployment rate - males % 2001 6.4 20.5 9f Unemployment rate - females % 2001 8.5 18.6 10 Youth unemployment/population ratio % 2000Q2 7.6 10.2 11t Long-term unemployment rate - total % 2001 3.2 12.6 11m Long-term unemployment rate - males % 2001 2.8 13.2 11f Long-term unemployment rate -females % 2001 3.9 11.9 12 Social protection expenditure as a percentage of GDP % 2000 27.3 : 13 Old age and survivors benefits as a percentage of total social benefits % 2000 46.4 : 14 Active public expenditure in LMP as a percentage of GDP % 2000 0.681 : 15 Inequality of income distribution Ratio 1998 5.4 : 16a Risk-of-poverty rate before social transfers % 1998 26 : 16b Risk-of-poverty rate after social transfers % 1998 18 : 17 Population in jobless households % 2000 4.5 : 18 Female share in national Parliaments % 1998 23° : 19m Employment rate - males (cf. nr. 7) % 2001 73.0 52.6 19f Employment rate - females (cf. nr. 7) % 2001 54.9 46.8 20 Gender pay gap in unadjusted form % 1999 84 : 21am Life expectancy at birth - males Years 2000 75.3 68.5 21af Life expectancy at birth - females Years 2000 81.4 75.1 21bm Healthy life years - males Years 1996 63 : 21bf Healthy life years - femalesYears 1996 66 : 22at Serious accidents at work - total Index points (1998 = 100) 2000 99* 100~b 22am Serious accidents at work - males Index points (1998 = 100) 2000 98* : 22af Serious accidents at work - females Index points (1998 = 100) 2000 104* : 22b Fatal accidents at work Index points (1998 = 100) 2000 79* 100~b Nr. Key indicator Unit Year EU-15 BG CY CZ EE HU LT MT PL RO SK SI 17.3 1.5 19.8 0.6 22.7 0.2 21.4° 0.0 22.6 -0.8 LV 20.2 0.0 18.1 3.5 17.8 -0.5 19.6 -0.2 16.5 0.3 20.2 1.4 TR : : 14.8 : 14.5 13.2 : 14.2 : 7.3 21.3 : 8.3 : 18.2 : 17.5 13.4 : 18.6 : 9.1 21.4 : 10.3 : 12.0 3.4 3.4 3.4 : : : : 11.4 5.3 4.0 6.3 12.9 3.0 2.5 3.5 : : : : 10.0 3.7 2.4 4.9 : : : : 5.6 5.2 4.6 5.9 21.3 1.1 1.1 1.0 : : : : 6.3 3.7 3.4 4.0 : : : : 65.9° 65.1 61.3 56.5 58.7 60.1° 54.2 55.0° 62.4 56.8 63.8 50.6 49.2° 37.1 48.4 24.1 36.9 41.6° 31.0 28.4° 48.2 22.4 25.5 34.1 67.3° 52.6 56.6 34.9 46.2 51.8° 52.5 36.7° 54.3 37.7 35.9 50.8 32.0° 23.2 42.1 15.3 30.0 33.9° 11.3 21.4° 42.9 9.8 15.8 18.4 : : : : : : : : : : : : : : : : : : : : : : : : : 4.5 3.0 6.5 : 8.0 6.8 9.9 : 12.3 12.0 12.5 : 5.7 6.4 5.0 : 12.8 14.1 11.6 : 16.1 18.4 13.8 : 6.8 6.2 8.2 : 18.6 17.2 20.3 : 6.8 7.3 6.3 : 19.7 20.5 18.8 : 6.0 5.7 6.3 : 8.5 8.8 7.9 4.0 7.5 8.5 4.6 8.2 10.1 : 13.4 7.4 16.5 6.1 : 1.2° 4.3 6.2 2.6 7.4 8.1° 2.9 7.4° 3.3 11.3 3.7 2.4 0.5° 3.5 6.8 3.0 8.3 9.9° 3.3 6.0° 3.5 11.3 3.5 : 2.1° 5.2 5.4 2.1 6.4 6.2° 1.7 9.1° 3.0 11.3 4.0 : : : : : : : : : : 20.0 26.6 : : : : : : : : : : 38.4 45.2 : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1.5 4.2 5.7 4.0 : : : : 3.8 8.9 2.6 : : 15 18 8 : : 9 13 : : 12 : 79.1° 73.3 65.5 63.4 61.9 61.9° 76.4 61.2° 67.8 62.0 68.6 74.3 53.2° 57.0 57.3 49.8 55.7 58.5° 31.6 48.9° 57.1 51.8 58.8 26.7 : : : : : : : : : : : : 75.3° 71.7 65.6 67.2 65.0 67.5 75.1 69.7 67.7 69.2 72.3 66.5° 80.4° : : 78.4 : : 76.4 : : 75.7 : : 76.1 : : 77.7 : : 79.3 : : 77.9 : : 74.6 : : 77.4 : : 79.7 : : 71.2° : : 112 91 105 94 66 94 94 79 106 88 98 85 : : : : : : : : : : : : : : : : : : : : : : : : 46* 96 56 95 90 78 41* 97 103 71 83 68~b CY CZ EE * = The figure may be from another year (latest available) or may have some other limitation. 195 HU LV LT MT PL RO SK SI TR Annex III Key social indicators per acceding/candidate country Reading note for each key indicators 3 EU-wide, the number of persons aged 65 and over corresponded to 24.3% of what is considered to be the working age population (15-64 years) in 2001. 4 The net migration rate for the EU in 2001 was 3.1 per 1000 inhabitants. 5t In 2001, 19.4% of 18-24 year-olds in the EU had left the education system without completing a qualification beyond lower secondary schooling. 6t EU-wide, 8.4% of the population aged 25-64 had participated in education/training in the 4 weeks prior to the survey in 2001. 7 64.0% of the EU population aged 15-64 were in employment in 2001. 8at 38.6% of the EU population aged 55-64 were in employment in 2001. 8bt In 2001, the effective average exit age from the labour market was 59,9 years. 9t 7.4% of the EU labour force (those at work and those seeking work) were unemployed in 2001. 10 7.3% of the EU population aged 15-24 were unemployed in 2001. 11t 3.2% of the EU labour force (those at work and those seeking work) had been unemployed for at least one year in 2001. 12 In 2000, EU social protection expenditure represented 27.3% of Gross Domestic Product (GDP). 13 EU-wide, old-age and survivors benefits make up the largest item of social protection expenditure (46.4% of total benefits in 2000). 14 In 2000, EU public expenditure on active Labour Market Policy measures represented 0.681% of Gross Domestic Product (GDP). 15 As an average in EU Member States in 1999, the top (highest income) 20% of a Member State's population received 4.6 times as much of the Member State's total income as the bottom (poorest) 20% of the Member State's population. 16a EU-wide before social transfers, 24% of the population would have been living below the poverty line in 1999. 16b EU-wide after social transfers, 15% of the population were actually living below the poverty line in 1999. 17a EU-wide in 2002, 12.1% of population aged 0-65 years were living in households with no member in employment (excluding persons in households where all members are aged less than 18 years, or 18-24 years and in education, or 65 years and more and not working). 18 EU-wide, 23% of the seats in the national Parliaments (or Lower House) were occupied by women in 2001. 19 73.0% / 54.9 % of the EU male / female population aged 15-64 were in employment in 2001. 20 EU-wide, the average gross hourly earnings of women were 84% of the average gross hourly earnings of men in 1999. The population consists of all paid employees aged 16-64 that are 'at work 15+ hours per week'. 21a The average life expectancy at birth of a male / female citizen in the EU was 75.3 / 81.4 years in 2000. 21b On average, a male / female citizen in the EU should live to 63 / 66 without disability (1996 data). 22at 22b EU-wide there occurred 1 % less serious working accidents (resulting in more than three days' absence) per 100 000 persons in employment in 2000 than in 1998. EU-wide there occurred 21 % less fatal working accidents per 100 000 persons in employment in 2000 than in 1998. 196 Statistical data - European Union acceding/candidate countries Annex IV Annex IV: Statistical data - European Union acceding/candidate countries More statistical data on candidate countries can be found in the "Statistical yearbook on candidate and South-East European counties". Eurostat. 2002. ISBN 92-894-3487-2 (paper and PDF). 1 ECONOMY Bulgaria Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Romania Slovak Slovenia Republic Turkey BG CY CZ EE HU LV LT MT PL RO SK SI TR 10.2 63.3 6.2 57.8 8.5 13.4 4.0 196.7 44.4 22.8 20.9 164.6 5.4 4.0 5.1 4.0 3.3 3.3 7.1 5.0 5.2 3.7 6.8 7.7 3.8 5.9 4.8 -0.4 4.0 1.1 1.8 5.3 2.2 3.3 4.6 3.0 7.4 -7.4 3.2 2.8 2.8 3.2 2.9 3.8 4.4 1.2 0.5 3.1 3.9 2.2 1.9 5.3 0.6 2.5 7.0 3.1 4.9 6.9 2.2 1.0 5.7 4.0 3.2 8.2 Gross domestic product at current market prices 2001. Bn Euro 15.2 GDP growth rates. at constant prices (1995) Annual growth rate. 2000 Annual growth rate. 2001 Compared to the same quarter of the previous year. 2002Q1 Compared to the same quarter of the previous year. 2002Q2 Growth rates for 2002Q1 and 2002Q2 are calculated from seasonally adjusted data. GDP per head (Index EU-15=100. in PPS) 1995 2001 33 28 83 77 62 57 34 42 46 51 25 33 32 38 53 : 34 40 28 25 46 48 63 69 27 22 6 500 17 800 13 300 9 800 11 800 7 700 8 700 : 9 200 5 900 11 100 16 000 5 200 : : : 17.9 : 16.2 16.8 : : 43.6 : : 11.0 : : : 18.9 : 16.0 17.6 : : 43.2 : : 11.3 GDP per head in PPS 2001 Net national income per head 2001. EU-15 = 100 Household consumption per head 2001. EU-15 = 100 Household consumption includes the consumption expenditure of non-profit institutions serving households. Net saving per head 2001. EU-15 = 100 (f) = forecast : : 280 (f) 220 : 320 210 : : : : 850 100 (f) : : 22.2 17.9 : 13.6 17.7 (f) 46.5 : : : 47.0 : Gross compensation per employee 2001. EU-15 = 100 (f) = forecast Gross compensation per employee includes wages and salaries plus employers’ social contributions. Gross compensation of employees is measured according to the domestic concept. while the number of employees is taken from the national concept. This has a significant effect on the ratio for countries with a relatively high proportion of workers living in neighbouring countries. Source: Eurostat - National Accounts. General government debt (% of GDP) 1999 2000 2001 79.3 73.6 66.3 : : : 14.5 17.0 23.7 6.5 5.1 4.8 61.0 55.4 53.1 13.7 13.9 16.0 23.0 24.0 23.1 59.9 60.7 65.7 42.7 38.7 39.3 24.0 24.0 23.3 40.2 45.2 44.1 26.4 27.6 27.5 66.0 56.0 103.0 : : : -3.2 -3.3 -5.5 -4.0 -0.4 0.2 -5.3 -3.0 -4.1 -5.3 -2.7 -1.6 -5.6 -2.7 -1.9 -8.3 -7.0 -7.0 -1.5 -1.8 -3.9 -4.5 -4.5 -3.4 -6.4 -12.8 -5.6 -2.2 -3.2 -2.5 -19.0 -6.0 -29.0 5.9 4.2 3.9 3.3 9.4 5.5 4.8 4.5 3.2 2.1 0.9 1.1 1.0 0.7 -0.3 0.3 : : : : 4.8 1.5 1.2 1.3 31.8 24.5 24.0 23.0 7.8 3.1 2.5 2.0 9.0 7.6 6.9 7.5 : : : : 4.5 6.4 2.8 1.8 : 3.1 27.4 4.9 7.8 : General government deficit (-) (% of GDP) 1999 2000 2001 0.2 -0.6 1.7 Source: Eurostat - National and Financial Accounts. Annual inflation rate compared to the same month of the previous year July 2001 May 2002 June 2002 July 2002 8.5 6.9 5.2 5.5 0.9 2.3 2.1 3.8 5.5 2.1 0.9 0.2 12-month average annual inflation rate. 12-month average rate July 2002 6.4 2.3 3.2 The annual inflation rate measures the price change between the current month and the same month the previous year. This measure is responsive to recent changes in price levels but can be influenced by one-off effects in either month. The 12-month average rate overcomes this volatility by comparing average Harmonized Indices of Consumer Prices (HICPs) in the latest 12 months to the average of the previous 12 months. This measure is less sensitive to transient changes in prices. Source: Eurostat - Price statistics. 197 Annex IV Statistical data - European Union acceding/candidate countries 1 ECONOMY (Contd.) BG CY CZ EE HU LV LT MT PL RO SK SI TR 6.21 5.76 5.66 5.65 11.85 7.55 7.59 7.26 : : : : 7.95 7.76 : : : : : : : : : : 7.23 5.83 5.79 6.13 : : 11.73 10.68 : : : : : : : 8.02 : : : : : : : : Interest rates: 10-year government bond yields (EMU convergence criterion series), monthly average August 2001 June 2002 July 2002 August 2002 : 8.27 7.87 7.68 : : : : 6.76 4.92 4.53 : 7.76 7.37 7.45 7.30 : : : : 7.99 6.00 6.00 5.14 Interest rates: 10-year government bond yields (EMU convergence criterion series), annual average 1996 1999 2000 2001 : : : : : 7.36 7.55 7.66 : : : 6.29 : : : : : 9.86 8.54 7.94 Source: Eurostat - Financial indicators. 198 : : : : : : : : Statistical data - European Union acceding/candidate countries Annex IV 2 POPULATION BG CY 830 846 150 107 : 608 759 : CZ EE HU LV LT MT 756 404 693 681 327 330 383 384 -1.6 -1.3 -0.3 6.8 3.3 3.5 PL RO SK SI TR 580 893 990 995 27 120 44 016 65 783 : 1.2 -0.2 1.4 14.8 14.8 0.0 Total population (1000) 1.1.1960 1.1.1980 1.1.2001. revised estimate 1.1.2002. first esimate 7 8 8 8 9 10 10 10 638 316 295 275 1 1 1 1 209 472 367 360 9 10 10 9 961 709 005 973 2 2 2 2 104 509 366 352 2 3 3 3 29 35 38 38 480 413 644 629 18 22 22 22 319 133 431 390 3 4 5 5 970 963 402 403 1 1 1 1 Population growth rates (per 1000 population), 2000 Total increase Natural increase Net migration -5.1 -5.1 0.0 5.9 4.5 1.5 -1.1 -1.8 0.6 -3.7 -3.9 0.2 -3.8 -3.8 0.0 -5.8 -5.0 -0.8 -0.2 0.3 -0.5 -1.1 -0.9 -0.2 0.7 0.4 0.3 The increase in total population is made up of the natural increase (live births less deaths) and net migration. Net migration is estimated on the basis of the difference between population change and natural increase (corrected net migration). Population structure (percentage of total), 2000 Total 0-19 20-59 60-79 80 and over 100 22.8 55.5 19.6 2.1 100 31.3 53.4 12.9 2.5 100 23.4 58.4 15.9 2.3 100 25.5 54.2 17.7 2.6 100 23.6 56.7 17.2 2.4 100 25.3 54.1 18.1 2.5 100 27.1 54.4 16.0 2.5 100 : : : : 100 28.3 55.2 14.6 1.9 100 26.0 55.3 16.9 1.7 100 28.1 56.5 13.5 1.8 100 23.2 57.8 16.8 2.3 100 41.4 50.7 7.2 0.5 15 811 2 931 648 12 232 1 665 509 40 1 116 9 397 : 1 013 8 384 2 913 1 242 : : 3 682 1 146 11 2 525 937 453 : : : : : : 6 600 : 2 220 4 380 : : : : 8 982 1 093 209 7 680 : : : : 1 491 686 19 786 4 982 911 17 4 054 3 454 955 131 2 368 9 677 1 257 : : 3 780 1 323 4 2 453 73 73 : : : : : : 19 945 : 11 790 8 155 : : : : 6 254 807 221 5 226 : : : : 14 320 2 245 629 11 446 - 3 317 - 402 23 - 2 938 5 943 : 882 6 016 - 6 764 - 15 : : - 98 - 177 7 72 864 380 : : : : : : - 13 345 : - 9 570 - 3 775 : : : : 2 728 286 - 12 2 454 : : : : 1 439 : : : : 10 043 9 890 153 18 135 2 424 1 805 620 1 619 3 699 : : : : 380 372 9 : : 38 654 : : : : 22 455 22 454 1 5 399 : : : : 1 988 1 945 43 1 41 64 814 : : : : TR: 1998. Immigration by main group of citizenship, 1997 Total Nationals Nationals of EU Member States Others : : : : 6 560 411 2 243 3 906 Emigration by main group of citizenship, 1997 Total Nationals Nationals of EU Member State Non EU nationals : : : : 8 000 : : : Net migration by main group of citizenship, 1997 Total Nationals Nationals of EU Member State Non EU nationals : : : : -1 440 : : : Source: Eurostat - Migration Statistics. Population by main group of citizenship, in thousands, 2000 Total Nationals Foreigners Nationals of EU Member State Non EU nationals 8 191 : : : : 755 731 24 : : 10 448 10 209 239 17 222 Source: Eurostat - Demographic Statistics and Council of Europe. TR: 61,000 foreigners in 1986. Population living in private households by household type, 2000 Total population : : 100 100 100 : : : : 100 100 100 : 1 adult without dependent children ... aged under 30 ... aged 30-64 ... aged 65 or more ... Male ... ... aged under 30 ... ... aged 30-64 ... ... aged 65 or more ... Female ... ... aged under 30 ... ... aged 30-64 ... ... aged 65 or more : : : : : : : : : : : : : : : : : : : : : : : : 8 1 3 4 3 0 1 1 5 0 2 4 10 1 5 4 3 1 2 1 7 1 3 3 9 1 4 5 3 0 2 1 6 0 2 4 : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 7 1 3 4 2 0 1 1 5 0 2 3 5 0 2 3 1 0 1 1 3 0 1 2 8 1 3 4 3 0 2 1 5 0 2 4 : : : : : : : : : : : : 199 Annex IV Statistical data - European Union acceding/candidate countries 2 POPULATION (Contd.) BG CY CZ EE HU LV LT MT PL RO SK SI TR 2 adults without dependent children ... both younger 65 ... at least one aged 65 or more : : : : : : 21 12 10 18 10 8 20 11 9 : : : : : : : : : : : : 16 8 8 13 6 6 17 9 8 : : : 3 or more adults without dependent children 1 adult with dependent children 2 adults with dependent children … 1 child … 2 children … 3 or more children : : : : : : : : : : : : 15 4 39 12 21 6 11 6 38 14 16 8 14 4 37 12 18 7 : : : : : : : : : : : : : : : : : : : : : : : : 12 2 37 13 17 7 17 2 32 8 16 8 21 3 33 13 17 3 : : : : : : 3 or more adults with dependent children : : 13 17 16 : : : : 26 31 18 : Note: Dependent children include all children younger than 15 years plus all those persons aged 15-24 who are economically inactive (mainly in education) and who are living with at least one of their parents. Source: Eurostat - European Labour Force Survey 2000. Crude marriage rate (per 1 000 population) 1960 1970 1980 1990 2000 8.8 8.6 7.9 6.7 4.2 : 8.6 7.9 9.3 12.3 7.7 9.2 7.6 8.8 5.4 10.0 9.1 8.8 7.5 4.0 8.9 9.3 7.5 6.4 4.8 11.0 10.2 9.8 8.8 3.9 10.1 9.5 9.2 9.8 4.6 5.9 7.4 8.6 7.1 6.2 8.3 8.6 8.6 6.7 5.5 10.7 7.2 8.2 8.3 6.1 8.1 7.9 7.9 7.6 4.8 8.9 8.3 6.5 4.3 3.7 : : 8.2 8.2 7.7 3.07 2.40 2.32 2.09 1.20 2.18 2.10 2.11 1.46 1.25 6.18 5.68 4.36 2.99 2.50 The crude marriage rate is the ratio of the number of marriages to the mean population in a given year. TR: 1998 data instead of 2000 data. Total fertility rate 1960 1970 1980 1990 2000 2.31 2.18 2.05 1.81 1.25 3.51 2.54 2.46 2.42 1.83 2.11 1.91 2.10 1.89 1.14 : 2.16 2.02 2.05 1.39 2.02 1.98 1.91 1.87 1.33 : 2.01 1.90 2.02 1.24 2.60 2.40 2.00 2.00 1.33 3.62 2.02 1.99 2.05 : 2.98 2.20 2.28 2.04 1.34 2.33 2.89 2.45 1.83 1.30 The total fertility rate is the average number of children that would be born alive to a woman during her lifetime if current fertility rates were to continue. Percentage of live births outside marriage 1960 1970 1980 1990 2000 8.0 9.3 10.9 12.4 38.4 0.2 0.2 0.6 0.7 2.1 4.9 5.4 5.6 8.6 21.8 : 14.1 18.3 27.1 54.5 5.5 5.4 7.1 13.1 29.0 11.9 11.4 12.5 16.9 40.3 7.3 6.4 6.3 7.0 22.6 0.7 1.5 1.1 1.8 10.1 4.5 5.0 4.7 6.2 11.7 : : : : 25.5 4.7 6.2 5.7 7.6 18.3 9.1 8.5 13.1 24.5 37.1 : : 2.9 4.4 : 1.3 2.2 2.6 3.1 2.9 2.1 3.2 4.1 3.7 3.1 1.7 2.2 2.6 2.4 2.4 2.4 4.6 5.0 4.0 2.6 0.9 2.2 3.2 3.4 2.9 : : : : : 0.5 1.1 1.1 1.1 1.1 2.0 0.4 1.5 1.4 1.4 0.6 0.8 1.3 1.7 1.7 1.0 1.1 1.2 0.9 1.1 0.4 0.3 0.4 0.5 0.5 CY 1998. MT and PL 1999 data instead of 2000 data. Crude divorce rate (per 1 000 population) 1960 1970 1980 1990 2000 : 1.2 1.5 1.3 1.2 : 0.3 0.3 0.6 1.7 The crude divorce rate is the ratio of the number of divorces to the mean population in a given year. BG, TR: 1999 data instead of 2000 data. Source: Eurostat - Demographic Statistics. TR: partly also Council of Europe. 200 Statistical data - European Union acceding/candidate countries Annex IV 3 EDUCATION AND TRAINING BG CY CZ EE HU LV LT MT PL RO SK SI TR : : : : 6 42 33 18 4 37 39 19 : : : : 6 40 31 23 : : : : : : : : 2 34 42 23 : : : : 10 47 31 13 : : : : Population aged 18-24 by activity status (%), 2000 In education and employment : In education and not in employment : Not in education and in employment : Not in education and not in employment: 4 30 52 14 Population aged 25-64 by age group, sex and educational attainment level (%), 2000 25-64 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 25-29 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 30-49 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education 32.9 48.7 18.4 37.0 37.8 25.2 13.9 74.6 11.5 15.3 56.3 28.5 30.8 55.2 14.0 16.5 65.3 18.1 15.1 42.6 42.3 : : : 20.3 68.3 11.4 30.7 60.1 9.2 16.4 73.3 10.2 25.2 59.1 15.7 : : : 33.4 51.1 15.5 33.2 38.8 28.0 8.8 78.1 13.1 16.6 61.9 21.6 25.9 60.4 13.7 18.3 65.1 16.6 15.0 47.5 37.5 : : : 18.5 71.4 10.1 24.2 65.4 10.4 11.4 77.7 10.9 20.8 65.1 14.1 : : : 32.5 46.4 21.1 40.8 36.8 22.4 19.0 71.1 9.9 14.1 51.2 34.7 35.3 50.4 14.3 14.9 65.6 19.5 15.3 38.1 46.6 : : : 22.0 65.4 12.6 37.0 54.9 8.1 21.3 69.1 9.6 29.6 53.0 17.3 : : : 25.1 56.8 18.1 18.9 47.0 34.1 6.9 82.9 10.2 12.6 55.3 32.1 19.1 66.8 14.0 13.4 70.6 16.0 11.0 52.9 36.1 : : : 9.8 75.2 15.0 14.9 76.1 9.0 5.0 84.0 10.9 12.1 68.0 20.0 : : : 27.0 61.7 11.3 18.9 50.8 30.2 5.7 84.7 9.7 17.7 59.7 22.6 17.8 70.3 11.9 14.6 71.1 14.4 12.6 56.4 31.0 : : : 10.8 78.1 11.1 13.7 76.6 9.7 4.9 85.2 9.9 14.1 73.3 12.6 : : : 22.9 51.5 25.6 18.9 43.4 37.8 8.1 81.2 10.7 7.7 51.0 41.3 20.5 63.2 16.3 12.2 70.2 17.6 9.4 49.3 41.4 : : : 8.7 72.3 19.0 16.1 75.6 8.3 5.2 82.8 12.0 10.0 62.6 27.3 : : : 25.6 54.0 20.5 29.4 41.7 29.0 11.8 75.4 12.8 8.5 63.0 28.6 22.7 62.6 14.7 9.5 70.9 19.6 4.8 47.9 47.3 : : : 14.6 74.5 10.9 20.4 70.0 9.6 12.5 76.5 11.0 22.8 61.5 15.7 : : : 26.6 56.4 17.0 27.2 40.9 31.9 8.1 77.3 14.6 10.1 70.1 19.8 18.6 68.1 13.2 11.4 72.3 16.3 6.3 52.6 41.1 : : : 14.2 76.2 9.6 15.6 74.1 10.3 9.2 79.1 11.7 19.8 66.5 13.7 : : : 24.5 51.6 23.9 31.5 42.5 26.0 15.6 73.4 11.0 6.9 56.0 37.1 26.7 57.2 16.1 7.7 69.6 22.7 3.4 43.3 53.3 : : : 15.0 72.9 12.1 25.1 66.1 8.8 15.8 73.9 10.3 25.9 56.3 17.8 : : : 50-64 years ..Males and Females ….Less than upper secondary ….Upper secondary ….Tertiary education ..Males ….Less than upper secondary ….Upper secondary ….Tertiary education ..Females ….Less than upper secondary ….Upper secondary ….Tertiary education : : 47.1 37.6 15.3 59.6 26.5 14.0 20.3 69.6 10.1 27.6 45.6 26.8 48.5 38.5 12.9 29.1 54.2 16.7 36.0 28.0 36.0 : : : 35.9 53.4 10.7 56.5 34.9 8.6 30.5 61.2 8.3 35.1 50.9 14.0 : : : 46.9 38.1 14.9 51.1 29.7 19.3 11.4 76.1 12.4 28.1 47.5 24.4 42.2 42.4 15.4 32.8 49.0 18.3 34.1 32.1 33.8 : : : 31.0 58.3 10.6 45.5 43.8 10.7 19.9 70.2 9.9 25.5 58.9 15.6 : : : 47.3 37.1 15.6 67.7 23.4 8.9 28.6 63.5 7.9 27.2 44.1 28.7 53.9 35.2 10.9 26.3 58.2 15.6 37.5 24.9 37.6 : : : 40.2 49.1 10.8 66.5 26.8 6.7 39.6 53.4 7.0 44.2 43.3 12.4 : : : The levels of education are defined according to ISCED (International Standard Classification of Education). Less than upper secondary corresponds to ISCED 0-2, upper secondary level to ISCED 3-4 (including thus post-secondary non-tertiary education) and tertiary education to ISCED 5-6. Unemployment rates of the population aged 25-59 by sex and level of education, 2000 Males and Females ..Less than upper secondary ..Upper secondary ..Tertiary education Males ..Less than upper secondary ..Upper secondary ..Tertiary education Females ..Less than upper secondary ..Upper secondary ..Tertiary education 24 14 6 7 4 3 20 7 3 22 15 5 10 6 1 21 15 7 23 20 9 : : : 23 14 5 5 8 4 37 15 4 10 6 2 : : : 22 13 7 5 2 2 22 5 2 23 15 6 12 6 1 23 15 7 27 21 10 : : : 21 12 5 6 7 4 44 15 5 11 6 1 : : : 26 14 6 9 8 3 19 9 3 22 15 4 9 5 1 17 14 8 17 18 8 : : : 24 17 5 4 8 3 32 15 3 10 6 3 : : : Participation (%) in education and training in the last four weeks of those aged 25-64 by sex and educational attainment level, 2000 201 Annex IV Statistical data - European Union acceding/candidate countries 3 EDUCATION AND TRAINING (Contd.) Males and Females ..Less than upper secondary ..Upper secondary ..Tertiary education Males ..Less than upper secondary ..Upper secondary ..Tertiary education Females ..Less than upper secondary ..Upper secondary ..Tertiary education BG CY CZ EE HU LV LT MT PL RO SK SI TR : : : : : : : : : : : : 3 1 2 8 3 1 2 8 3 0 3 9 : : : : : : : : : : : : 6 0 4 13 4 0 3 9 8 0 5 15 3 1 3 8 3 1 3 7 3 0 4 9 : : : : : : : : : : : : 3 0 2 5 2 0 1 4 3 0 2 6 : : : : : : : : : : : : : : : : : : : : : : : : 1 0 1 1 1 0 1 1 1 0 1 1 : : : : : : : : : : : : 4 1 5 8 4 1 4 7 5 1 5 9 : : : : : : : : : : : : 82 83 79 84 82 85 75 83 78 84 59 51 83 88 58 62 : : 83 89 33 24 Source: Eurostat - European Union Labour Force Survey. Participation rates (16-18 year olds) by sex. 1998/99 Males Females 63 66 : : CY: no population data for males and females. SK: no breakdown by age. TR: 228844 students in ISCED 3C cannot be broken down by age or gender. Data for ISCED 3C relates to the 1997/98 educational year. Females per 100 males in tertiary education 1998/99 147 127 99 137 118 160 150 106 133 104 107 127 66 22 22 22 22 22 22 22 23 22 22 22 23 21 21 21 21 22 21 23 23 22 22 22 22 : : : 22 23 22 22 22 22 RO. SI: ISCED 6 missing Median age of students in tertiary education. 1998/99 Males and Females Males Females 22 23 22 21 21 20 RO. SI: ISCED 6 missing Source: Eurostat - UOE (Unesco. OECD and Eurostat questionnaires on education statistics). 202 Statistical data - European Union acceding/candidate countries Annex IV 4 LABOUR MARKET BG CY CZ EE HU LV LT MT PL RO SK SI TR 60.6 64.3 57.1 55.9 62.7 49.4 58.2 62.3 54.3 60.1 61.8 58.5 : : : 55.1 61.2 49.3 64.2 69.5 59.0 56.3 61.6 51.1 62.7 66.7 58.5 : : : Employment rate. 15-64 years, by sex, second quarter of 2000 Total Males Females 51.5 56.1 47.2 65.5 78.9 52.5 64.9 73.1 56.8 Employment rate by age-group and sex, second quarter of 2000 Males and Females ...50-54 ...55-59 ...60-64 Males ...50-54 ...55-59 ...60-64 Females ...50-54 ...55-59 ...60-64 65.6 33.5 10.5 71.3 60.5 35.1 80.4 50.2 16.9 73.6 58.4 29.4 66.4 33.7 7.6 69.9 49.3 21.8 72.8 56.8 26.4 : : : 61.4 37.7 20.9 70.3 56.6 48.0 69.0 34.5 6.1 64.4 29.0 15.1 : : : 67.6 53.6 15.7 91.0 80.8 50.0 84.5 71.6 23.5 72.5 66.5 35.5 69.7 50.2 10.8 69.9 64.5 31.6 69.3 64.3 38.4 : : : 65.7 47.5 27.5 77.4 63.1 52.5 74.4 55.3 10.4 77.7 40.3 19.8 : : : 63.8 16.2 6.1 51.8 40.7 21.5 76.3 30.4 11.2 74.5 52.0 24.8 63.2 19.8 5.1 69.9 37.5 14.9 75.8 50.8 17.7 : : : 57.4 28.9 15.4 63.3 51.1 44.1 63.9 16.8 2.7 51.2 17.5 11.2 : : : 19.6 20.5 18.6 4.5 3.0 6.5 : : : 12.3 12.0 12.5 5.7 6.3 4.9 12.9 14.2 11.5 16.5 19.0 13.8 6.8 6.2 8.2 18.6 17.2 20.3 6.5 7.0 5.9 19.7 20.5 18.8 5.9 5.6 6.3 : : : Unemployment rate by sex, 2001 Total Males Females Youth unemployment/population ratio (aged 15-24) by sex, second quarter of 2000 Total Males Females 10.2 13.0 7.6 4.0 2.8 5.1 7.5 8.3 6.6 8.5 10.3 6.7 4.6 5.9 3.4 8.2 9.4 6.9 10.1 11.5 8.8 : : : 13.4 13.8 13.0 7.4 8.8 5.9 16.5 19.1 13.9 6.1 6.0 6.2 : : : : 17.4 16.4 24.6 24.7 22.4 10.9 13.7 10.4 22.6 21.1 21.3 31.3 27.6 27.4 16.7 : : 42.0 34.3 37.2 17.0 19.3 15.9 38.5 40.0 33.3 16.9 14.8 18.5 : : : 8.4 9.0 7.8 8.8 10.9 6.7 : : : 8.0 6.5 9.8 3.6 3.9 3.2 11.3 11.4 11.1 4.5 4.5 4.4 : : : : : : 26.5 24.0 29.4 13.1 14.2 11.8 28.8 31.5 25.9 11.9 9.9 14.6 : : : Youth unemployment rate (aged 15-24) by sex, 2001 Total Males Females 39.5 36.1 29.6 9.6 6.7 14.2 Long-term unemployment rate (12 months or more), second quarter of 2000 Total Males Females 10.2 10.4 9.9 1.3 0.5 2.5 4.5 3.7 5.5 6.7 7.7 5.7 3.2 3.8 2.6 Youth long-term unemployment rate (aged 15-24. 6 months or more), second quarter of 2000 Total Males Females 25.8 28.0 22.9 4.9 2.3 7.5 11.8 11.9 11.7 12.8 14.0 11.1 8.5 9.8 6.8 13.7 13.4 14.1 20.4 21.5 18.9 Employment rates represent persons in employment aged 15-64 as a percentage of the population of the same age. Persons in employment are those who during the reference week (of the Labour Force Survey) did any work for pay or profit for at least one hour or were not working but had jobs from which they were temporarily absent. Unemployed people - according to the International Labour Organisation (ILO) criteria are those persons aged 15 and over who are i) without work, ii) available to start work within the next two weeks and, iii) have actively sought employment at some time. Unemployment rates represent unemployed persons as a percentage of the active population of the same age. The active population is defined as the sum of persons in employment and unemployed persons. Source: Eurostat - European Union Labour Force Survey. 203 Annex IV Statistical data - European Union acceding/candidate countries 5 SOCIAL PROTECTION BG CY CZ EE HU LV LT MT PL RO SK SI TR : : : : : : : : : : : : : : 20.4 20.0 26.6 26.6 : : : : : : : : 2097 4057 : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 38.4 32.9 8.0 4.6 9.3 6.8 45.2 30.7 9.0 4.3 9.2 1.6 : : : : : : Expenditure on social protection as a percentage of GDP 1998 1999 : : : : : : Expenditure on social protection in PPS per head of population, 2000 Total : : : : Social benefits by group of functions (as a percentage of total social benefits), 2000 Old age and survivors benefits Sickness. healthcare Disability Unemployment Family and children Housing and social exclusion n.e.c. : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Receipts of social protection by type (as a percentage of total receipts), 2000 General government contributions Employers' social contributions Social contributions paid by protected persons Other receipts : : : : : : : : : : : : : : : : : : : : 27.0 48.5 31.5 27.0 : : : : : : : : : : : : : : : : : : : : : : 18.6 5.9 39.3 2.2 : : LV LT MT PL RO SK SI TR 4.39 4.46 4.70 : 2.08 2.28 2.87 3.15 104.95 125.60 106.95 : 1.35 1.40 1.37 1.51 3.88 4.18 4.37 4.56 1.67 : : : The abbreviation 'n.e.c.' indicates not elsewhere classified. Source: Eurostat - European system of integrated social protection statistics (ESSPROS). 6 INCOME, POVERTY AND SOCIAL EXCLUSION BG CY CZ EE HU Average gross hourly earnings in industry (Manual workers, sections C to F of NACE Rev. 1) in ECU 1997 1998 1999 2000 80.38 105.66 114.02 128.45 : 6.20 6.36 : 1.73 1.89 1.91 2.20 1.28 1.42 1.53 : 1.83 1.85 2.03 2.21 1.26 1.35 1.46 1.68 0.98 1.20 1.27 1.48 BG. RO: monthly earnings. CZ: excluding construction. Average gross monthly earnings of full-time employees in industry and services (sections C to K of NACE Rev. 1) in ECU 1997 1998 1999 2000 76 100 109 127 1181 1240 1342 : 309 339 359 400 242 276 291 323 277 289 318 348 198 214 226 270 190 233 251 299 759 764 836 : 323 346 442 490 111 136 120 : 269 280 271 286 768 823 809 860 382 407 : : 7 GENDER EQUALITY BG CY CZ EE HU LV LT MT PL RO SK SI TR Female share in national parliaments (Percentage of seats occupied by women in the national parliaments (or Lower House)) Year Percentage : : : : 1998 15.2 1999 17.8 1998 8.4 : : : : 1998 9.2 1997 13.4 : : : : 1996 12.2 : : : : : : 1998 0.0 1999 13.3 2000 6.1 : : : : 1998 7.1 1999 10.5 : : : : 1997 5.6 : : 78.0 77.8 74.3 : 75.2 75.0 77.5 76.9 73.7 83.2 83.8 83.8 86.3 90.3 : : : : : : : Female share in national governments Year Percentage Source: European database - Women in decision making (www.db-decision.de). Average monthly earnings of women as percentage of men's in industry and services (sections C to K of NACE Rev. 1) 1995 1996 1997 1998 1999 2000 : 72.9 74.1 73.5 77.6 74.6 69.5 70.0 70.2 68.7 69.3 : : 77.2 75.7 72.0 74.2 73.3 73.3 72.6 72.0 74.2 : : 80.3 79.0 77.6 81.4 81.3 81.0 : 78.4 79.9 80.1 77.8 76.9 76.9 81.3 78.4 78.4 80.7 80.9 : : : : 76.4 : 77.7 77.8 80.2 83.2 82.6 : 81.9 79.5 CZ: Full-time employees. sections A to O of NACE Rev.1. EE: Hourly earnings. all activities. LV: Data from short-term statistics. bonuses included. PL: Source: the representative survey in September of 1995 to 1997 or as of October 1998-1999. RO: Earnings of women as a percentage of men for the month of October; bonuses included. Source: Annual survey on earnings by occupations for the month of October. SI: All activities; if only industry: 80.6 (1998). 204 Statistical data - European Union acceding/candidate countries Annex IV 8 HEALTH AND SAFETY BG CY CZ EE HU LV LT MT PL RO SK SI TR 27.3 13.3 26.0 6.1 20.2 4.1 17.7 8.4 35.9 9.2 17.7 10.4 19.3 8.6 27.9 6.1 36.4 8.1 49.4 18.6 24.5 8.6 25.7 4.9 : : 68.7 68.5 72.3 75.3 66.8 71.7 64.1 65.6 65.5 67.2 63.5 65.0 65.5 67.5 68.5 75.1 66.9 69.7 66.5 67.7 66.8 69.2 67.4 72.3 55.8 66.5 74.0 75.1 77.0 80.4 73.9 78.4 74.1 76.4 72.7 75.7 74.2 76.1 75.4 77.7 72.7 79.3 75.4 77.9 71.8 74.6 74.3 77.4 75.2 79.7 60.4 71.2 Infant mortality rate, per 1000 live births 1970 2000 CY: 1998 Life expectancy at birth, males 1980 2000 CY: 1999; TR: 1998. Life expectancy at birth, females 1980 2000 CY: 1999; TR: 1998. Source: Eurostat - Demographic Statistics. TR: Council of Europe. Standardised death rates (SDR) per 100 000 population by sex, 1999 Males Diseases of the circulatory system Cancer Diseases of the respiratory system External causes of injury and poisoning Females Diseases of the circulatory system Cancer Diseases of the respiratory system External causes of injury and poisoning 877 203 64 : : : 603 320 55 783 282 62 745 402 79 812 303 55 647 287 70 406 236 113 597 299 72 836 217 104 671 336 74 424 295 112 : : : 83 : 91 271 141 261 244 41 112 102 98 120 : 607 121 33 : : : 402 179 28 442 144 14 477 205 34 477 139 16 415 140 18 324 137 52 374 153 30 625 126 56 442 156 34 269 156 45 : : : 24 : 34 59 50 69 57 17 31 30 23 39 : : : 1348 1103 1154 717 1009 837 1245 938 1402 885 : 547 575 514 605 554 : 1116 243 257 Data 1998 except PL 1996 Source: WHO - Health For All Database 2002 Hospital beds per 100 000 inhabitants 1990 1999 1004 748 Number of persons per 100 000 discharged from hospitals by ICD diagnosis, 2000 Infectious and parasitic diseases Cancer Diseases of the respiratory system Diseases of the circulatory system Mental and behavioural disorders External causes of injury and poisoning 505 522 1781 1766 : : : : : : 467 1494 1567 3271 302 674 1555 2165 3118 : 395 1810 2201 4084 1524 1040 1464 3094 3939 1291 748 1233 2441 3060 1607 : : : : : : : : : : 990 1091 3008 2253 : 480 1658 1292 1671 543 490 1377 1606 2723 594 295 258 725 732 86 1036 : 1740 1282 1487 2141 2213 : : 1188 1639 1495 341 9.0 : 9.2 : 8.1 6.2 : 7.8 : Source: Eurostat - Health and safety statistics. Prevalence per 1000 for Alzheimer’s and other dementias, 2000 Source: Alzheimer Europe and Eurostat 6.1 3.6 9.5 : Total expenditure on health (percentage of Gross Domestic Product) 1990 2000 5.2 4.7 : : 5.0 7.3 : 6.1 6.1 6.8 2.5 4.8 3.3 6.2 : 8.8 5.3 6.2 2.8 2.6 5.6 7.9 5.4 6.5 3.6 4.8 111 113 111 1 360 1 455 1 486 284 232 204 1 371 1 306 1 200 627 604 588 829 748 641 17 4 15 7 080 6 730 6 294 2 778 2 505 2 499 860 671 647 309 334 313 6 083 5 723 5 510 120 248 173 39 163 111 120 157 84 92 168 11 60 86 32 53 : Data 2000 except BG: 1994. PL: 1999. RO, TR: 1998 Source: WHO - Health For All Database 2002 Number of persons killed in road accidents 1998 1999 2000 1 003 1 047 1 012 Number of persons killed in road accidents per million inhabitants 2000 124 165 144 149 Source: Eurostat - Transport Statistics. Home and leisure accidents (age standardised mortality rate per 100 000 inhabitants), 1995 55 : 40 177 70 Source: WHO mortality statistics,1995 205 Annex IV Statistical data - European Union acceding/candidate countries 9 CONSUMPTION BG CY CZ EE HU LV LT MT PL RO SK SI TR More statistical data on consumption can be found in "Consumers in Europe – Facts and figures 1996-2000", Eurostat. 2001. ISBN 92-894-1400-6. Final consumption expenditure of households, 2000, current prices Thousand millions of euro Euro per inhabitant Thousand millions of PPS PPS per inhabitant Percentage of GDP 9 1 100 37 4 500 71.6 5 8 300 8 : : 30 2 900 73 7 100 53.7 3 2 200 7 5 000 57.7 26 2 600 59 5 900 51.1 5 2 000 10 4 200 62.5 8 2 100 18 4 800 64.1 : : : : : 110 2 800 219 5 700 64.0 28 1 200 82 3 700 70.0 11 2 000 31 5 700 52.9 11 5 300 17 8 400 54.0 : : : : : 100 : : : CY: 1998. Source: Eurostat. National Accounts - ESA95 - aggregates (theme2/aggs) Estimation of structure of household consumption expenditure, 1999 (%) Total 100 Food and non-alcoholic beverages 46.5 Alcoholic beverages and tobacco 3.9 Clothing and footwear 8.2 Housing. water. electricity. gas and other fuels (1) 14.2 Furnishings. household equipment & routine maintenance 4.4 Health (2) 3.3 Transport (3) 7.2 Communication (4) 1.9 Recreation and culture 3.0 Education 0.6 Restaurants and hotels 3.5 Miscellaneous goods and services 3.3 100 : : : 100 25.2 3.5 7.7 100 35.7 3.4 7.7 100 28.9 4.3 6.6 100 42.1 2.8 7.1 100 48.1 4.0 8.0 100 : : : 100 35.1 3.3 7.0 100 55.3 2.7 7.4 100 33.0 3.6 10.3 100 26.1 3.4 8.4 : 17.1 18.7 19.5 17.0 12.3 : 18.4 15.3 12.4 10.7 : : : : : : : : : 7.8 1.5 10.2 2.0 11.0 0.6 5.0 8.4 5.4 1.6 6.8 2.8 7.5 1.2 3.5 5.7 5.4 3.0 9.2 4.4 6.7 0.4 3.0 8.6 4.2 3.5 6.9 3.2 5.6 1.0 2.5 4.1 4.8 3.5 6.7 1.9 3.5 0.3 3.8 2.9 : : : : : : : : 5.5 4.4 8.6 2.3 6.5 1.3 1.3 6.3 4.3 2.3 5.2 1.4 2.6 0.6 0.8 2.1 6.4 1.2 8.9 2.1 8.2 0.5 5.8 7.6 6.8 1.6 16.5 1.9 8.8 0.7 5.9 9.2 : : : : : : : : CZ: Estimations based on the national classification of the 9 main expenditure groups. EE: Non-monetary consumption of non-food items is not included; own produced food or food received without paying is included. SI: 1997. (1) Imputed rent for owner-occupiers is not included in any of the countries; CZ, HU and SI, housing provided by employer (for free or reduced price) is not included; CZ. the benefit from free or reduced cost supply of gas, electricity and water is not included; LT, LV and PO. measurement problems. (2) HU, LT and PL, household net expenditure (after deduction of social security and private insurance reimbursements) is recorded; in the other countries, household gross expenditure is recorded; LT, all expenditures of households are recorded, except for accommodation in sanatoriums; PL. health expenditure is not corrected for reimbursement; for the other countries, information on recording is not available. (3) RO, SI and SK. personal use of a company car and/or free fuel is not accounted for; LV, LT and PL, measurement problems. (4) CZ: free or reduced telephone costs are not included; LV, LT and PO, measurement problems. Source: Eurostat - Household Budget Survey (theme3/hbs) Percentage of dwellings with selected electrical appliances, 1996 (%) Cooker Microwave oven Fridge Freezer Automatic washing machine Non-automatic washing machine Clothes dryer Dishwasher Hot water boiler Space heater Air conditioning 86.4 4.4 88.5 17.3 40.6 36.2 0.3 0.9 61.1 83.4 0.4 : : : : : : : : : : : 16.3 30.1 98.1 65.2 74.7 35.7 3.3 3.3 38.8 20.5 0.4 47.8 11.0 89.7 11.7 22.6 52.1 : 0.7 11.3 25.4 : 9.7 25.8 99.9 52.4 43.9 59.6 0.4 0.6 47.1 9.3 0.4 6.1 2.8 86.6 2.2 8.6 61.3 : 0.1 3.1 93.6 : 11.0 5.4 93.7 6.2 11.6 63.2 : 2.0 2.1 6.5 : : : : : : : : : : : : : : 100.0 30.0 50.0 80.0 : : : : : 2.7 : 68.9 13.0 7.2 43.6 : : 0.3 11.9 : 30.1 18.1 97.4 55.7 57.0 45.7 1.2 1.3 30.0 14.4 0.2 86.0 6.9 95.2 85.8 96.4 : 7.2 20.2 47.3 17.4 0.7 : : : : : : : : : : : : : : : 21 24 : : PL: Based on households rather than dwellings; 1993. SI: Automatic washing machines includes non-automatic washing machines. Source: Eurostat - Survey on Energy Consumption in Households Level of internet access - households - Percentage of households who have Internet access at home 2000 2001 : : 14 20 8 11 7 10 2.6 : Source: Eurostat - Information Society Statistics 206 : 2 2.3 3.2 11.2 : : 8.2 Symbols, countries, abbreviations and acronyms Annex V Annex V: Symbols, countries and country groupings, other abbreviations and acronyms Symbols * ~b u : . 0 % ° provisional/estimated data or low reliability due to small number of observations break in time series unreliable or uncertain data not available nil not applicable or data not statistically significant less than half the unit used percent see the note (the figure may be from another year or may have some other limitation) Countries and country groupings EU-15 The 15 Member States of the European Union EUR-12 The euro zone with 12 countries participating (B, D, EL, E, F, IRL, I, L, NL, A, P and FIN) The 'southern' Member States are EL, E, I and P. The 'Nordic' Member States are DK, FIN and S. B E L FIN Belgium Spain Luxembourg Finland DK F NL S Denmark France Netherlands Sweden D IRL A UK Germany Ireland Austria United Kingdom EL Greece I Italy P Portugal CZ LT SK Czech Republic Lithuania Slovak Republic EE Estonia MT Malta SI Slovenia Acceding states /candidate countries: BG HU PL TR Bulgaria Hungary Poland Turkey CY Cyprus LV Latvia RO Romania Other abbreviations and acronyms CVT CVTS2 EC ECB ECHP ECHP UDB ESAW ESSPROS EU Eurostat GCSE GDP HBS HICP ICD ILO ISCED LLL LFS LMP NACE Rev. 1 n.e.c. NUTS OECD PPS QLFD SES SDR UOE UNESCO Continuing Vocational Training Second Survey of Continuing Vocational Training European Communities European Central Bank European Community Household Panel European Community Household Panel – Users’ Database European Statistics on Accidents at Work European System of integrated Social Protection Statistics European Union the Statistical Office of the European Communities General Certificate of Secondary Education Gross Domestic Product Household Budget Survey Harmonised Index on Consumer Prices International Classification of Diseases and Health Related Problems International Labour Organisation International Standard Classification of Education Lifelong Learning Labour Force Survey Labour Market Policy Statistical Classification of Economic Activities in the European Community not elsewhere classified Nomenclature of Territorial Units for Statistics Organisation for Economic Co-operation and Development Purchasing Power Standard Quarterly Labour Force Data Structure of Earnings Survey Standardised Death Rate UNESCO/OECD/Eurostat United Nations Educational, Scientific and Cultural Organisation 207 Eurostat Data shops Annex VI Annex VI: Eurostat Datashops Belgique/ België France Eurostat Data Shop Bruxelles/Brussel Planistat Belgique Rue du Commerce 124 Handelsstraat 124 B-1000 Bruxelles/Brussel Tel. (32-2) 234 67 50 Fax (32-2) 234 67 51 E-mail: [email protected] URL: http://www.datashop.org/ INSEE Info service Eurostat Data Shop 195, rue de Bercy Tour Gamma A F-75582 Paris Cedex 12 Tel. (33) 1 53 17 88 44 Fax (33) 1 53 17 88 22 E-mail: [email protected] Member of the MIDAS Net Languages spoken: FR Languages spoken: ES, DE, EN, FR Danmark Italia - Roma DANMARKS STATISTIK Bibliotek og Information Eurostat Data Shop Sejrøgade 11 DK-2100 København Ø Tel. (45) 39 17 30 30 Fax (45) 39 17 30 03 E-mail: [email protected] Internet: http://www.dst.dk/bibliotek Languages spoken: IT Languages spoken: DA, EN Deutschland Italia - Milano ISTAT Ufficio regionale per la Lombardia Eurostat Data Shop Via Fieno, 3 I-20123 Milano Tel. (39) 02 80 61 32 460 Fax (39) 02 80 61 32 304 E-mail: [email protected] Member of the MIDAS Net Statistisches Bundesamt Eurostat Data Shop Berlin Otto-Braun-Straße 70-72 (Eingang: Karl-Marx-Allee) D-10178 Berlin Tel. (49) 1888-644 94 27/28 Fax (49) 1888-644 94 30 E-Mail: [email protected] URL: http://www.eu-datashop.de/ Languages spoken: IT Languages spoken: DE, EN España ISTAT Centro di informazione statistica — Sede di Roma Eurostat Data Shop Via Cesare Balbo, 11a I-00184 Roma Tel. (39) 06 46 73 31 02/06 Fax (39) 06 46 73 31 01/07 E-mail: [email protected] Member of the MIDAS Net Luxembourg INE Eurostat Data Shop Paseo de la Castellana, 183 Despacho 011B Entrada por Estébanez Calderón E-28046 Madrid Tel. (34) 91 583 91 67 / 91 583 95 00 Fax (34) 91 583 03 57 E-mail: [email protected] URL: http://www.datashop.org/ Member of the MIDAS Net Eurostat Data Shop Luxembourg 46A, avenue J.F. Kennedy B.P. 1452 L-1014 Luxembourg Tel. (352) 43 35-2251 Fax (352) 43 35-22221 E-mail: [email protected] URL: http://www.datashop.org/ Member of the MIDAS Net Languages spoken: ES, DE, EN, FR,IT Nederland Languages spoken: ES, EN, FR STATISTICS NETHERLANDS Eurostat Data Shop — Voorburg Postbus 4000 2270 JM Voorburg Nederland Tel. (31-70) 337 49 00 Fax (31-70) 337 59 84 E-mail: [email protected] Languages spoken: EN, NL 209 Annex VI Eurostat Data shops Portugal Norge Eurostat Data Shop Lisboa INE/Serviço de Difusão Av. António José de Almeida, 2 P-1000-043 Lisboa Tel. (351) 21 842 61 00 Fax (351) 21 842 63 64 E-mail: [email protected] Languages spoken: EN, FR, PT Statistics Norway Library and Information Centre Eurostat Data Shop Kongens gate 6 Boks 8131 Dep. N-0033 Oslo Tel. (47) 21 09 46 42/43 Fax (47) 21 09 45 04 E-mail: [email protected] Languages spoken: EN, NO Suomi/Finland STATISTICS FINLAND Eurostat DataShop Helsinki Tilastokirjasto PL 2B FIN-00022 Tilastokeskus Työpajakatu 13 B, 2. Kerros, Helsinki Tel. (358-9) 17 34 22 21 Fax (358-9) 17 34 22 79 E-mail: Sähköposti: [email protected] URL: http://tilastokeskus.fi/tk/kk/datashop/ Schweiz/Suisse/ Svizzera Statistisches Amt des Kantons Zürich Eurostat Data Shop Bleicherweg 5 CH-8090 Zürich Tel. (41) 1 225 12 12 Fax (41) 1 225 12 99 E-mail: [email protected] URL: http://www.statistik.zh.ch Languages spoken: EN, FI, SV Languages spoken: DE, EN Sverige STATISTICS SWEDEN Information service Eurostat Data Shop Karlavägen 100 Box 24 300 S-104 51 Stockholm Tel. (46-8) 50 69 48 01 Fax (46-8) 50 69 48 99 E-mail: [email protected] URL: USA http://www.scb.se/tjanster/datashop/datashop.asp HAVER ANALYTICS Eurostat Data Shop 60 East 42nd Street Suite 3310 New York, NY 10165 United States Tel. (1-212) 986 93 00 Fax (1-212) 986 69 81 E-mail: [email protected] Languages spoken: EN, SV Languages spoken: EN United Kingdom Eurostat Data Shop Office for National Statistics Room 1.015 Cardiff Road Newport South Wales NP10 8XG United Kingdom Tel. (44) 1633 813369 Fax (44) 1633 813333 E-mail: [email protected] Eurostat home page www.europa.eu.int/comm/eurostat/ Languages spoken: EN 210 European Commission The social situation in the European Union — 2003 Luxembourg: Office for Official Publications of the European Communities 2003 — 210 pp. — 21 x 29.7 ISBN 92-894-5263-3 ISSN 1681-1658 Price (excluding VAT) in Luxembourg: 25 EUR